diff --git a/devel_test/README.md b/devel_test/README.md
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--- /dev/null
+++ b/devel_test/README.md
@@ -0,0 +1 @@
+This directory is for interim tests during the development process.
diff --git a/devel_test/temporal_average_daily.ipynb b/devel_test/temporal_average_daily.ipynb
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--- /dev/null
+++ b/devel_test/temporal_average_daily.ipynb
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+{
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+   "cell_type": "markdown",
+   "id": "ab1d3dea-b953-4e53-a94d-ab9a2d1ab39c",
+   "metadata": {},
+   "source": [
+    "# Temporal Average Testing\n",
+    "\n",
+    "Test procedure:\n",
+    "- XCDAT is source-installed from branch `feature/201-temporal-mean`\n",
+    "- PR: https://github.com/xCDAT/xcdat/pull/236\n",
+    "\n",
+    "## Load test data -- daily, 6 yr dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "ac226d47-9fdc-4f9c-b2ff-d9542b23c5f2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "a0ba4da0-603f-4437-ab82-7b3fa9a7c2d2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "demo_data_dir = '../tutorials/demo_data/CMIP5_demo_timeseries/historical/atmos/day/pr'\n",
+    "demo_filename = 'pr_day_GISS-E2-H_historical_r6i1p1_20000101-20051231.nc'\n",
+    "demo_file = os.path.join(demo_data_dir, demo_filename)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "8a67df64-9f0b-4515-8fdc-2122a2eddd1c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import xcdat"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "c20b0719-f1a3-4781-a8af-465c05cf4240",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds = xcdat.open_dataset(demo_file)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "d965ac21-d875-4951-bb2d-70a6dedade3a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pr = ds.pr"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "1b9227cd-3c9a-4135-8228-b3b17eabe81c",
+   "metadata": {},
+   "outputs": [
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+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (time: 2190, lat: 90, lon: 144)&gt;\n",
+       "[28382400 values with dtype=float32]\n",
+       "Coordinates:\n",
+       "  * time     (time) object 2000-01-01 12:00:00 ... 2005-12-31 12:00:00\n",
+       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
+       "  * lon      (lon) float64 1.25 3.75 6.25 8.75 11.25 ... 351.2 353.8 356.2 358.8\n",
+       "Attributes:\n",
+       "    standard_name:     precipitation_flux\n",
+       "    long_name:         Precipitation\n",
+       "    comment:           at surface; includes both liquid and solid phases from...\n",
+       "    units:             kg m-2 s-1\n",
+       "    original_name:     dummy\n",
+       "    cell_methods:      time: mean\n",
+       "    cell_measures:     area: areacella\n",
+       "    history:           2013-04-18T19:18:11Z altered by CMOR: replaced missing...\n",
+       "    associated_files:  baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'pr'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 2190</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 144</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-dce35bc2-0614-43d7-b3d8-8661a0f30191' class='xr-array-in' type='checkbox' checked><label for='section-dce35bc2-0614-43d7-b3d8-8661a0f30191' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[28382400 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-ce9fbcb3-fa66-4f27-83b2-bd571c742d20' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ce9fbcb3-fa66-4f27-83b2-bd571c742d20' 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'>object</div><div class='xr-var-preview xr-preview'>2000-01-01 12:00:00 ... 2005-12-...</div><input id='attrs-490e0cff-91c5-437a-9d34-5ac28d774508' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-490e0cff-91c5-437a-9d34-5ac28d774508' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1fca086d-e8a3-454e-9b07-4c14ff4cb053' class='xr-var-data-in' type='checkbox'><label for='data-1fca086d-e8a3-454e-9b07-4c14ff4cb053' 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([cftime.DatetimeNoLeap(2000, 1, 1, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2000, 1, 2, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2000, 1, 3, 12, 0, 0, 0, has_year_zero=True), ...,\n",
+       "       cftime.DatetimeNoLeap(2005, 12, 29, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2005, 12, 30, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2005, 12, 31, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</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'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-e62b58da-19d4-4270-879a-9b4b4584be1f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e62b58da-19d4-4270-879a-9b4b4584be1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22c473e0-5359-42b8-bb2a-144bebbfdff0' class='xr-var-data-in' type='checkbox'><label for='data-22c473e0-5359-42b8-bb2a-144bebbfdff0' 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., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
+       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
+       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
+       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
+       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
+       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
+       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
+       "        79.,  81.,  83.,  85.,  87.,  89.])</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'>1.25 3.75 6.25 ... 356.2 358.8</div><input id='attrs-33852048-a61a-41f3-8346-4f92230841f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-33852048-a61a-41f3-8346-4f92230841f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a803c9d-97d7-4390-9bcd-bcecb717e167' class='xr-var-data-in' type='checkbox'><label for='data-2a803c9d-97d7-4390-9bcd-bcecb717e167' 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([  1.25,   3.75,   6.25,   8.75,  11.25,  13.75,  16.25,  18.75,  21.25,\n",
+       "        23.75,  26.25,  28.75,  31.25,  33.75,  36.25,  38.75,  41.25,  43.75,\n",
+       "        46.25,  48.75,  51.25,  53.75,  56.25,  58.75,  61.25,  63.75,  66.25,\n",
+       "        68.75,  71.25,  73.75,  76.25,  78.75,  81.25,  83.75,  86.25,  88.75,\n",
+       "        91.25,  93.75,  96.25,  98.75, 101.25, 103.75, 106.25, 108.75, 111.25,\n",
+       "       113.75, 116.25, 118.75, 121.25, 123.75, 126.25, 128.75, 131.25, 133.75,\n",
+       "       136.25, 138.75, 141.25, 143.75, 146.25, 148.75, 151.25, 153.75, 156.25,\n",
+       "       158.75, 161.25, 163.75, 166.25, 168.75, 171.25, 173.75, 176.25, 178.75,\n",
+       "       181.25, 183.75, 186.25, 188.75, 191.25, 193.75, 196.25, 198.75, 201.25,\n",
+       "       203.75, 206.25, 208.75, 211.25, 213.75, 216.25, 218.75, 221.25, 223.75,\n",
+       "       226.25, 228.75, 231.25, 233.75, 236.25, 238.75, 241.25, 243.75, 246.25,\n",
+       "       248.75, 251.25, 253.75, 256.25, 258.75, 261.25, 263.75, 266.25, 268.75,\n",
+       "       271.25, 273.75, 276.25, 278.75, 281.25, 283.75, 286.25, 288.75, 291.25,\n",
+       "       293.75, 296.25, 298.75, 301.25, 303.75, 306.25, 308.75, 311.25, 313.75,\n",
+       "       316.25, 318.75, 321.25, 323.75, 326.25, 328.75, 331.25, 333.75, 336.25,\n",
+       "       338.75, 341.25, 343.75, 346.25, 348.75, 351.25, 353.75, 356.25, 358.75])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-77c75b3e-7639-481e-8eae-069aba6b2d80' class='xr-section-summary-in' type='checkbox'  checked><label for='section-77c75b3e-7639-481e-8eae-069aba6b2d80' class='xr-section-summary' >Attributes: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitation</dd><dt><span>comment :</span></dt><dd>at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>original_name :</span></dt><dd>dummy</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>history :</span></dt><dd>2013-04-18T19:18:11Z altered by CMOR: replaced missing value flag (-1e+30) with standard missing value (1e+20).</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_GISS-E2-H_historical_r0i0p0.nc areacella: areacella_fx_GISS-E2-H_historical_r0i0p0.nc</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'pr' (time: 2190, lat: 90, lon: 144)>\n",
+       "[28382400 values with dtype=float32]\n",
+       "Coordinates:\n",
+       "  * time     (time) object 2000-01-01 12:00:00 ... 2005-12-31 12:00:00\n",
+       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
+       "  * lon      (lon) float64 1.25 3.75 6.25 8.75 11.25 ... 351.2 353.8 356.2 358.8\n",
+       "Attributes:\n",
+       "    standard_name:     precipitation_flux\n",
+       "    long_name:         Precipitation\n",
+       "    comment:           at surface; includes both liquid and solid phases from...\n",
+       "    units:             kg m-2 s-1\n",
+       "    original_name:     dummy\n",
+       "    cell_methods:      time: mean\n",
+       "    cell_measures:     area: areacella\n",
+       "    history:           2013-04-18T19:18:11Z altered by CMOR: replaced missing...\n",
+       "    associated_files:  baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation..."
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pr"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "51bf1c04-a1fd-4e5b-a560-1d74405ce66f",
+   "metadata": {},
+   "source": [
+    "## 1. Temporal Average\n",
+    "\n",
+    "### 1.1 Default (`center_times=False`, `weighted=True`)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "553043f8-3982-4300-b026-6e4a73ad05b9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_ave_month = ds.temporal.average(\"pr\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "347e0e12-418c-4644-94dc-b405eedcaeb7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_ave_month = ds.temporal.average(\"pr\", weighted=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "40e19a21-cf46-46cf-ab5e-a48682008d40",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(90, 144)"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_ave_month.pr.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "c20553c6-3095-4e91-944e-125ad3076731",
+   "metadata": {},
+   "outputs": [
+    {
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+       ".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:   (lat: 90, bnds: 2, lon: 144)\n",
+       "Coordinates:\n",
+       "  * lat       (lat) float64 -89.0 -87.0 -85.0 -83.0 ... 83.0 85.0 87.0 89.0\n",
+       "  * lon       (lon) float64 1.25 3.75 6.25 8.75 ... 351.2 353.8 356.2 358.8\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    lat_bnds  (lat, bnds) float64 -90.0 -88.0 -88.0 -86.0 ... 88.0 88.0 90.0\n",
+       "    lon_bnds  (lon, bnds) float64 0.0 2.5 2.5 5.0 ... 355.0 357.5 357.5 360.0\n",
+       "    pr        (lat, lon) float64 7.904e-07 7.904e-07 ... 3.448e-06 3.448e-06\n",
+       "Attributes: (12/27)\n",
+       "    institution:            NASA/GISS (Goddard Institute for Space Studies) N...\n",
+       "    institute_id:           NASA-GISS\n",
+       "    experiment_id:          historical\n",
+       "    source:                 GISS-E2-H-Eh135f9f Atmosphere: GISS-E2; Ocean: H\n",
+       "    model_id:               GISS-E2-H\n",
+       "    forcing:                GHG, LU, Sl, Vl, BC, OC, SA, Oz (also includes BC...\n",
+       "    ...                     ...\n",
+       "    table_id:               Table day (27 April 2011) 86d1558d99b6ed1e7a886ab...\n",
+       "    title:                  GISS-E2-H model output prepared for CMIP5 historical\n",
+       "    parent_experiment:      pre-industrial control\n",
+       "    modeling_realm:         atmos\n",
+       "    realization:            6\n",
+       "    cmor_version:           2.5.7</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-e52c052a-b233-4861-960a-d65b5ad8443d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e52c052a-b233-4861-960a-d65b5ad8443d' 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'>lat</span>: 90</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lon</span>: 144</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9808d219-5ab1-4265-9268-eb6ff821a63d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9808d219-5ab1-4265-9268-eb6ff821a63d' class='xr-section-summary' >Coordinates: <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 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'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-6a67af8b-fcec-49e2-b6fb-57180c7febaf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a67af8b-fcec-49e2-b6fb-57180c7febaf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-517cc6a0-5173-4380-8ca5-5bc9c02a0d8b' class='xr-var-data-in' type='checkbox'><label for='data-517cc6a0-5173-4380-8ca5-5bc9c02a0d8b' 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., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
+       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
+       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
+       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
+       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
+       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
+       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
+       "        79.,  81.,  83.,  85.,  87.,  89.])</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'>1.25 3.75 6.25 ... 356.2 358.8</div><input id='attrs-ba88084d-339c-4b36-a62c-65aeacf15167' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba88084d-339c-4b36-a62c-65aeacf15167' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f42842e6-9b7c-4973-b495-8b23f8b368ca' class='xr-var-data-in' type='checkbox'><label for='data-f42842e6-9b7c-4973-b495-8b23f8b368ca' 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([  1.25,   3.75,   6.25,   8.75,  11.25,  13.75,  16.25,  18.75,  21.25,\n",
+       "        23.75,  26.25,  28.75,  31.25,  33.75,  36.25,  38.75,  41.25,  43.75,\n",
+       "        46.25,  48.75,  51.25,  53.75,  56.25,  58.75,  61.25,  63.75,  66.25,\n",
+       "        68.75,  71.25,  73.75,  76.25,  78.75,  81.25,  83.75,  86.25,  88.75,\n",
+       "        91.25,  93.75,  96.25,  98.75, 101.25, 103.75, 106.25, 108.75, 111.25,\n",
+       "       113.75, 116.25, 118.75, 121.25, 123.75, 126.25, 128.75, 131.25, 133.75,\n",
+       "       136.25, 138.75, 141.25, 143.75, 146.25, 148.75, 151.25, 153.75, 156.25,\n",
+       "       158.75, 161.25, 163.75, 166.25, 168.75, 171.25, 173.75, 176.25, 178.75,\n",
+       "       181.25, 183.75, 186.25, 188.75, 191.25, 193.75, 196.25, 198.75, 201.25,\n",
+       "       203.75, 206.25, 208.75, 211.25, 213.75, 216.25, 218.75, 221.25, 223.75,\n",
+       "       226.25, 228.75, 231.25, 233.75, 236.25, 238.75, 241.25, 243.75, 246.25,\n",
+       "       248.75, 251.25, 253.75, 256.25, 258.75, 261.25, 263.75, 266.25, 268.75,\n",
+       "       271.25, 273.75, 276.25, 278.75, 281.25, 283.75, 286.25, 288.75, 291.25,\n",
+       "       293.75, 296.25, 298.75, 301.25, 303.75, 306.25, 308.75, 311.25, 313.75,\n",
+       "       316.25, 318.75, 321.25, 323.75, 326.25, 328.75, 331.25, 333.75, 336.25,\n",
+       "       338.75, 341.25, 343.75, 346.25, 348.75, 351.25, 353.75, 356.25, 358.75])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a15c22ae-6c0a-45dc-b5d1-4388b8957d0e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a15c22ae-6c0a-45dc-b5d1-4388b8957d0e' class='xr-section-summary' >Data variables: <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>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'>...</div><input id='attrs-53d7c22f-aff0-4e03-ad11-70d0b696f1a5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-53d7c22f-aff0-4e03-ad11-70d0b696f1a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-703cfdcc-b61d-420d-8102-7649c8d6202a' class='xr-var-data-in' type='checkbox'><label for='data-703cfdcc-b61d-420d-8102-7649c8d6202a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-90., -88.],\n",
+       "       [-88., -86.],\n",
+       "       [-86., -84.],\n",
+       "       [-84., -82.],\n",
+       "       [-82., -80.],\n",
+       "       [-80., -78.],\n",
+       "       [-78., -76.],\n",
+       "       [-76., -74.],\n",
+       "       [-74., -72.],\n",
+       "       [-72., -70.],\n",
+       "       [-70., -68.],\n",
+       "       [-68., -66.],\n",
+       "       [-66., -64.],\n",
+       "       [-64., -62.],\n",
+       "       [-62., -60.],\n",
+       "       [-60., -58.],\n",
+       "       [-58., -56.],\n",
+       "       [-56., -54.],\n",
+       "       [-54., -52.],\n",
+       "       [-52., -50.],\n",
+       "       [-50., -48.],\n",
+       "       [-48., -46.],\n",
+       "       [-46., -44.],\n",
+       "       [-44., -42.],\n",
+       "       [-42., -40.],\n",
+       "       [-40., -38.],\n",
+       "       [-38., -36.],\n",
+       "       [-36., -34.],\n",
+       "       [-34., -32.],\n",
+       "       [-32., -30.],\n",
+       "       [-30., -28.],\n",
+       "       [-28., -26.],\n",
+       "       [-26., -24.],\n",
+       "       [-24., -22.],\n",
+       "       [-22., -20.],\n",
+       "       [-20., -18.],\n",
+       "       [-18., -16.],\n",
+       "       [-16., -14.],\n",
+       "       [-14., -12.],\n",
+       "       [-12., -10.],\n",
+       "       [-10.,  -8.],\n",
+       "       [ -8.,  -6.],\n",
+       "       [ -6.,  -4.],\n",
+       "       [ -4.,  -2.],\n",
+       "       [ -2.,   0.],\n",
+       "       [  0.,   2.],\n",
+       "       [  2.,   4.],\n",
+       "       [  4.,   6.],\n",
+       "       [  6.,   8.],\n",
+       "       [  8.,  10.],\n",
+       "       [ 10.,  12.],\n",
+       "       [ 12.,  14.],\n",
+       "       [ 14.,  16.],\n",
+       "       [ 16.,  18.],\n",
+       "       [ 18.,  20.],\n",
+       "       [ 20.,  22.],\n",
+       "       [ 22.,  24.],\n",
+       "       [ 24.,  26.],\n",
+       "       [ 26.,  28.],\n",
+       "       [ 28.,  30.],\n",
+       "       [ 30.,  32.],\n",
+       "       [ 32.,  34.],\n",
+       "       [ 34.,  36.],\n",
+       "       [ 36.,  38.],\n",
+       "       [ 38.,  40.],\n",
+       "       [ 40.,  42.],\n",
+       "       [ 42.,  44.],\n",
+       "       [ 44.,  46.],\n",
+       "       [ 46.,  48.],\n",
+       "       [ 48.,  50.],\n",
+       "       [ 50.,  52.],\n",
+       "       [ 52.,  54.],\n",
+       "       [ 54.,  56.],\n",
+       "       [ 56.,  58.],\n",
+       "       [ 58.,  60.],\n",
+       "       [ 60.,  62.],\n",
+       "       [ 62.,  64.],\n",
+       "       [ 64.,  66.],\n",
+       "       [ 66.,  68.],\n",
+       "       [ 68.,  70.],\n",
+       "       [ 70.,  72.],\n",
+       "       [ 72.,  74.],\n",
+       "       [ 74.,  76.],\n",
+       "       [ 76.,  78.],\n",
+       "       [ 78.,  80.],\n",
+       "       [ 80.,  82.],\n",
+       "       [ 82.,  84.],\n",
+       "       [ 84.,  86.],\n",
+       "       [ 86.,  88.],\n",
+       "       [ 88.,  90.]])</pre></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'>...</div><input id='attrs-307690b9-13af-46e7-9d21-e5aac43d20b9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-307690b9-13af-46e7-9d21-e5aac43d20b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2324f8c1-fc3c-4e91-aae4-8f380e98eae9' class='xr-var-data-in' type='checkbox'><label for='data-2324f8c1-fc3c-4e91-aae4-8f380e98eae9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  0. ,   2.5],\n",
+       "       [  2.5,   5. ],\n",
+       "       [  5. ,   7.5],\n",
+       "       ...,\n",
+       "       [352.5, 355. ],\n",
+       "       [355. , 357.5],\n",
+       "       [357.5, 360. ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.904e-07 7.904e-07 ... 3.448e-06</div><input id='attrs-252b9809-7d4e-4ecd-bfaf-61a33c2fa300' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-252b9809-7d4e-4ecd-bfaf-61a33c2fa300' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2615b518-411c-4c7c-8b05-d5172596c006' class='xr-var-data-in' type='checkbox'><label for='data-2615b518-411c-4c7c-8b05-d5172596c006' 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>at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>original_name :</span></dt><dd>dummy</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>history :</span></dt><dd>2013-04-18T19:18:11Z altered by CMOR: replaced missing value flag (-1e+30) with standard missing value (1e+20).</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_GISS-E2-H_historical_r0i0p0.nc areacella: areacella_fx_GISS-E2-H_historical_r0i0p0.nc</dd><dt><span>operation :</span></dt><dd>temporal_avg</dd><dt><span>mode :</span></dt><dd>average</dd><dt><span>freq :</span></dt><dd>day</dd><dt><span>weighted :</span></dt><dd>True</dd><dt><span>center_times :</span></dt><dd>False</dd></dl></div><div class='xr-var-data'><pre>array([[7.90422321e-07, 7.90422321e-07, 7.90422321e-07, ...,\n",
+       "        7.90422321e-07, 7.90422321e-07, 7.90422321e-07],\n",
+       "       [1.40761676e-06, 1.47176690e-06, 1.59294996e-06, ...,\n",
+       "        1.56964630e-06, 1.48251336e-06, 1.40310309e-06],\n",
+       "       [2.18994881e-06, 1.95212633e-06, 1.82568941e-06, ...,\n",
+       "        3.02005329e-06, 2.73270763e-06, 2.42857161e-06],\n",
+       "       ...,\n",
+       "       [8.99962503e-06, 9.07416458e-06, 9.17712682e-06, ...,\n",
+       "        8.79387425e-06, 8.73545086e-06, 8.77054593e-06],\n",
+       "       [7.50127394e-06, 7.46026056e-06, 7.53139687e-06, ...,\n",
+       "        7.24340800e-06, 7.27545021e-06, 7.35771297e-06],\n",
+       "       [3.44792129e-06, 3.44792129e-06, 3.44792129e-06, ...,\n",
+       "        3.44792129e-06, 3.44792129e-06, 3.44792129e-06]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-787f700d-8cdd-4045-b7cb-86eff4358249' class='xr-section-summary-in' type='checkbox'  ><label for='section-787f700d-8cdd-4045-b7cb-86eff4358249' class='xr-section-summary' >Attributes: <span>(27)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>institution :</span></dt><dd>NASA/GISS (Goddard Institute for Space Studies) New York, NY</dd><dt><span>institute_id :</span></dt><dd>NASA-GISS</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>source :</span></dt><dd>GISS-E2-H-Eh135f9f Atmosphere: GISS-E2; Ocean: H</dd><dt><span>model_id :</span></dt><dd>GISS-E2-H</dd><dt><span>forcing :</span></dt><dd>GHG, LU, Sl, Vl, BC, OC, SA, Oz (also includes BC on snow - Nitrate aerosols)</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p1</dd><dt><span>branch_time :</span></dt><dd>2510.0</dd><dt><span>contact :</span></dt><dd>Kenneth Lo (cdkkl@giss.nasa.gov)</dd><dt><span>references :</span></dt><dd>http://data.giss.nasa.gov/modelE/ar5</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>b31006b5-e988-4b70-8908-858a18cfa2bb</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>day</dd><dt><span>creation_date :</span></dt><dd>2013-04-18T19:18:11Z</dd><dt><span>history :</span></dt><dd>2013-04-18T19:18:11Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table day (27 April 2011) 86d1558d99b6ed1e7a886ab3fd717b58</dd><dt><span>title :</span></dt><dd>GISS-E2-H model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>6</dd><dt><span>cmor_version :</span></dt><dd>2.5.7</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:   (lat: 90, bnds: 2, lon: 144)\n",
+       "Coordinates:\n",
+       "  * lat       (lat) float64 -89.0 -87.0 -85.0 -83.0 ... 83.0 85.0 87.0 89.0\n",
+       "  * lon       (lon) float64 1.25 3.75 6.25 8.75 ... 351.2 353.8 356.2 358.8\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    lat_bnds  (lat, bnds) float64 ...\n",
+       "    lon_bnds  (lon, bnds) float64 ...\n",
+       "    pr        (lat, lon) float64 7.904e-07 7.904e-07 ... 3.448e-06 3.448e-06\n",
+       "Attributes: (12/27)\n",
+       "    institution:            NASA/GISS (Goddard Institute for Space Studies) N...\n",
+       "    institute_id:           NASA-GISS\n",
+       "    experiment_id:          historical\n",
+       "    source:                 GISS-E2-H-Eh135f9f Atmosphere: GISS-E2; Ocean: H\n",
+       "    model_id:               GISS-E2-H\n",
+       "    forcing:                GHG, LU, Sl, Vl, BC, OC, SA, Oz (also includes BC...\n",
+       "    ...                     ...\n",
+       "    table_id:               Table day (27 April 2011) 86d1558d99b6ed1e7a886ab...\n",
+       "    title:                  GISS-E2-H model output prepared for CMIP5 historical\n",
+       "    parent_experiment:      pre-industrial control\n",
+       "    modeling_realm:         atmos\n",
+       "    realization:            6\n",
+       "    cmor_version:           2.5.7"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_ave_month"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "66e7ac8a-a4d2-428c-952f-427dde5cb6ab",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x163d390d0>"
+      ]
+     },
+     "execution_count": 11,
+     "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": [
+    "ds_ave_month.pr.plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "acf885d0-9298-4ad7-b9a1-28901cead816",
+   "metadata": {},
+   "source": [
+    "### 1.2 `weighted=False`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "435f61c7-be19-4e1f-bdee-3c3471378af4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_ave_month_nw = ds.temporal.average(\"pr\", weighted=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "ab0543ba-d8d5-4f70-bb63-44741cfcf2c4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x163eb2130>"
+      ]
+     },
+     "execution_count": 13,
+     "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": [
+    "(ds_ave_month.pr - ds_ave_month_nw.pr).plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "122d2caa-7c89-4bc2-9de9-802c7b33ec56",
+   "metadata": {},
+   "source": [
+    "### 1.3 `center_times=True`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "1bc848e3-3cf0-4460-a8e1-1044839d7561",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_ave_month_center = ds.temporal.average(\"pr\", center_times=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "371b253d-999d-4820-9c10-f48133d04b0e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(90, 144)"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_ave_month_center.pr.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "d207d41b-e09b-4bbc-a77c-84dd229a5b8b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x164029e50>"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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GAK8AtqTpOLLHYOdL+vQgg81jMvBw2fK2tK6CpAWS1kha0/+U3xcwsw7L31J+Yum3Kk0Lys6S5/eu1j65fisH6V3Ae4FbgDVlU0N5K+VfBLwhInYDSLqarMfh04D7BhttDtVquvb5WyAiFpO1j2H0kVP9voWZdc7gGjbujIhZNbbl+b2rtU+u38pBOpYsobwunevfgWvyHJg3oUwGxpI95iLNvyC9UvzM4GLNZRswtWx5CvBoG65jZta81vwZm+f3rtY+B+Q4drCWAL8ESlUd56Z1DSvr8yaUTwD3SrqZLCOeBPxDauj4/cFGm8OdwAxJ04FHyDqi/OM2XMfMrGktqkPJ83u3HLgg1ZGcADwREdsl/SzHsYP14oh4ednyTZLW5jkw71teX5S0gqzySMBHIqKUBT80qFDzXW93etNgJdAHXBsRG1p9HTOzIdkz9FPU+r2T9O60/RpgBTAH2Ar8Cjiv3rFDDOkeSSdGxG0Akk4AfpjnwLxveQk4BTgqIv5W0pGSZkfEHU2H3EBErCC7iWZmXSdvG5M8qv3epURSmg9qjJLbht/KE4A/kfRQWj4S2CTpvhTKcbUOzPvI6yqyXPwG4G+BJ4FvAMc3HbKZ2XA3MlvKn9HsgXkTygkRMVPSPQAR8d+SDmj2omZmI8IIfLc0Iv6r2WPzJpRnU4vM0ngoh9GSp4dmZsOXB9iqlLdh4xXADcDhki4FfgD8Q9uiMjMbDjymfIW8b3ldL+kusop5AWdHxKa2RmZm1s0C5Oc0FeomFEkTyhZ3AF8p35anbxczsxGrh0ofeTQqodzF3ub9RwL/neYPBR4CprczODOzbuY6lEp161AiYnpEHEXWaOYtETExIn6LbCwUD65lZmbPyVspf3xqPANARHwHeH17QjIzGyZcKV8h72vDOyX9FfBlstvzdrIRHM3MepMr5feRt4RyLnAY2avDN6T5c9sVlJnZsOASSoW8rw0/DlzY5ljMzIYN4Ur5geqWUCR9rNEJ8uxjZjYiuYRSoVEJ5U8l/bLOdpH1v/+xlkVkZjYctLC34ZGiUUL5PHBwjn3MzHqPE0qFugklIj7ergtLuhx4C7AL+AlwXkT8Im27BDgf6AfeHxEr2xWHmVmz/JZXpbxvebXDKuBlabCW/wQuAZB0LNljtJeS9ct/Verp2Mysu7gOpUJhCSUivhcRu9PibcCUND8XWBoRz0TEA2RDXs4uIkYzs5ryJhMnlI57F/CdND8ZeLhs27a0bh+SFkhaI2lN/1NPtzlEM7NKpWGAG029IldCkXSMpNWS1qfl41LL+UbHfV/S+irT3LJ9PgrsBq4vrapyqqr/JBGxOCJmRcSsvnFj83wVM7PWcQmlQt6uVz4PfAj4HEBErJP0r8Df1zsoIk6tt13SfLKOJk+JiNJt3wZMLdttCvBozjjNzDqml0ofeeR95HVQRNwxYN3uqnvmJOkM4MPAWRHxq7JNy4F5kkZLmg7MAAZe28ysWEE2EHqeqUcMpnPIo9k7pvw5wPYhXvuzwGhglSSA2yLi3RGxQdIyYCNZ0loYEf1DvJaZWUuJ6s/ne1nehLIQWAy8RNIjwANkPQ43LSJeVGfbpcClQzm/mVnb+ZFXhbydQ94PnCppLDAqIp5sb1hmZt3PdSiVGo0p/8Ea6wGIiE+2ISYzs+HBCaVCoxJKqR+vFwPHk1WYQ9Zlyq3tCsrMrOt5gK195OrLS9L3gJmlR12py/qvtT06M7Nu5hJKhbyV8keSdeJYsguY1vJozMyGEdehVMqbUL4E3CHpBrKc/PvAdW2LysxsOHBCqZD3La9LJX0H+N206ryIuKd9YZmZdT+XUCrlSiiSjgR2AjeUr4uIh9oVmJlZV+uxfrryyPvI6/+x99YdCEwHNpONWWJm1nOE3/IaKO8jr98pX5Y0E/jztkRkZjZcuIRSoanxUCLibrJ2KWZmPUsRuaYhXUOaIGmVpC3pc3yN/c6QtFnSVkmLytZfLunHktZJukHSoUMKqI6846F8sGy6KHVd/7N2BWVm1vU6N2LjImB1RMwAVqflCmmY9CuBM4FjgXPTcOpQY7j1dshbQjm4bBpNVqcyt+4RZmYjXIdGbJwLLEnzS4Czq+wzG9gaEfdHxC5gaTqu3nDrLZe3Un5jRFS0jJf0Vtxa3sx6WIcq5Y+IiO0AEbFd0uFV9qk2dPoJVfZ7F/DV1oeYyZtQLmHf5FFtnZlZ78hf+pgoaU3Z8uKIWFxakPR94PlVjvtozvM3HDq9ynDrLdeot+EzgTnAZElXlG06hCGO2Fh2jYuAy4HDImJnWncJcD7QD7w/Ila24lpmZi0zuMdZOyNiVs1T1RkuXdJjkial0skkYEeV3eoOnV5juPWWa1SH8iiwBvgNcFfZtBw4fagXlzQVOA14qGzdscA8sjYuZwBXpQonM7Pu0plK+eXA/DQ/H7ixyj53AjMkTZd0ANlv6HKoO9x6yzXqbXgtsFbS9WWVOq30KeBiKm/QXGBpRDwDPCBpK1mF04/acH0zs6aIjnW9chmwTNL5ZH98vxVA0guAL0TEnIjYLekCYCXQB1wbERvS8VWHW29HoI0eeS2LiD8E7pH2vXXpNbSmSDoLeCQi1pYG7Eomk72JULItrat2jgXAAoC+8VVfzTYza5/2PT0qu0T8HDilyvpHyaokSssrgBVV9qs53HqrNaqUvzB9vrmZkzeoaPoI8MZqh1VZV/VfLVVqLQYYfeRUt1k1s87xAFv7aPTIa3uafW9EfLh8m6R/JHsuV+/4qhVNkn6HrD+wUulkCnC3pNk0qFwyM+sWTiiV8jZsPK3KujObvWhE3BcRh0fEtIiYRpZEZkbET8kqkuZJGi1pOjADuKPZa5mZtU1nKuWHjUZ1KO8B3gscJWld2aaDgR+2I6CI2CBpGbCR7NXkhRHR345rmZkNhcdDqdSoDuVfge8A/4vK/mOejIjHWxVEKqWUL18KXNqq85uZtVzQkUr54aRRHcoTwBPAuQCpyf8YYJykcR5gy8x6mUsolfL2NvwWSVuAB4BbgAfJSi5mZj2pNMBWnqlX5K2U/3vgROA/I2I62TvRbalDMTMbFiLyTz0ib0J5NjWuGSVpVETcBLyifWGZmXW/DnVfP2zk7W34F5LGAbcC10vaQYs6hzQzG7Z6KFnkkbeEMhf4NfAXwHeBnwBvaVdQZmbDgUsolXKVUCLi6bLFJTV3NDPrFQH091C2yKFRw8YnqV6oExARcUhbojIzGwZ6qfSRR6N2KAd3KhAzs2Gnh97gyiNvpbyZmQ3gEkolJxQzs2b0WMePeTihmJk1IRux0RmlnBOKmVmT5Le8KjihmJk1w4+89uGEYmbWlN7qpyuPvC3l20LS+yRtlrRB0ifK1l8iaWvadnqRMZqZ1eKW8pUKK6FI+j2yLl2Oi4hn0lgrSDoWmAe8FHgB8H1Jx3jURjPrOi6hVCiyhPIe4LKIeAYgInak9XOBpRHxTEQ8AGwFZhcUo5lZdeHxUAYqMqEcA/yupNsl3SLp+LR+MvBw2X7b0jozs+6yJ/JNPaKtj7wkfR94fpVNH03XHk82cNfxwDJJR5G93j1Q1X8RSQuABQB948e3ImQzs9zcDqVSWxNKRJxaa5uk9wDfjIgA7pC0B5hIViKZWrbrFODRGudfDCwGGH3kVP/LmllnOaFUKPKR17eANwBIOgY4ANgJLAfmSRotaTowA7ijqCDNzKoKYE/OqUcU2Q7lWuBaSeuBXcD8VFrZIGkZsJFsVMiFfsPLzLqNCD/yGqCwhBIRu4C319h2KXBpZyMyMxukPT1U/MjBLeXNzJpReuRlz3FCMTNrkh95VXJCMTNrlhNKBScUM7OmuHPIgZxQzMyaETihDOCEYmbWJA+wVanQ7uvNzIa1iHzTEEiaIGmVpC3ps2o/U5LOSEN+bJW0qMr2iySFpIlDCqgOJxQzs2YEneocchGwOiJmAKvTcgVJfcCVwJnAscC5aSiQ0vapwGnAQ0MNph4nFDOzpuQsnQy9nmUusCTNLwHOrrLPbGBrRNyfGo0vTceVfAq4mDYPWuyEYmbWrPwJZaKkNWXTgkFc5YiI2J5dLrYDh1fZp+awH5LOAh6JiLVNfcdBcKW8mVmz8pc+dkbErFobGwz1kUfVYT8kHZTO8cac5xkSJxQzs2ZEQH9r+q1tMNTHY5ImRcR2SZOAHVV2qzXsx9HAdGCtpNL6uyXNjoiftiT4Mn7kZWbWrM7UoSwH5qf5+cCNVfa5E5ghabqkA4B5wPKIuC8iDo+IaRExjSzxzGxHMgEnFDOz5nTuLa/LgNMkbSF7U+syAEkvkLQCICJ2AxcAK4FNwLKI2DDUCw+WH3mZmTWrAy3lI+LnwClV1j8KzClbXgGsaHCuaa2Or5wTiplZs9z1SoXCHnlJeoWk2yTdm16jm1227ZLU2nOzpNOLitHMrKZSpXyeqUcUWUL5BPDxiPiOpDlp+eTUunMe8FLgBcD3JR3jYYDNrOu4hFKhyEr5AA5J888je8UNstadSyPimYh4ANhK1grUzKy7dOYtr2GjyBLKB4CVkv6JLLG9Jq2fDNxWtt9zLT4HSq1NFwD0ja/aX5qZWZu05A2uEaWtCaVB689TgL+IiG9I+kPgi8Cp1GjxWe38EbEYWAww+sip/pc1s84JiPCg8uXamlAatP68DrgwLX4N+EKar9Xi08ysu7iEUqHIOpRHgden+TcAW9L8cmCepNGSpgMzgDsKiM/MrDa/5bWPIutQ/gz4jKT9gN+Q6kIiYoOkZcBGYDew0G94mVlX6qEK9zwKSygR8QPgVTW2XQpc2tmIzMwGJ/a4DqWcW8qbmTWlt14JzsMJxcysGaXOIe05TihmZk0IIHqowj0PJxQzs2ZEgNuhVHBCMTNrUviRVwUnFDOzZrmEUkExQt5SkPQksLnoOAaYCOwsOogqujEux5SPY8qvXlwvjIjDhnJySd9N18hjZ0ScMZTrDQcjKaGsiYhZRcdRrhtjgu6MyzHl45jy69a4RjK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+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "(ds_ave_month.pr - ds_ave_month_center.pr).plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8a1d84d9-5689-4d39-8973-70ccb7fec98e",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## 2. Group Average"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7362bb1b-9a6a-4a75-9a0d-9ec0707da9bf",
+   "metadata": {},
+   "source": [
+    "### 2.1 Day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "ef6ab42f-c91b-4049-bd22-a027db7ea9a1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_gra_day = ds.temporal.group_average(\"pr\", freq=\"day\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "735e7f9d-c35e-481f-9639-c698acf6618a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(2190, 90, 144)"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_day.pr.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "b6bac77b-8a88-4c77-8d26-ee0a2470c05c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "  --xr-border-color: #1F1F1F;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-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.DataArray &#x27;pr&#x27; (lat: 90, lon: 144)&gt;\n",
+       "array([[0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       ...,\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)\n",
+       "Coordinates:\n",
+       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
+       "  * lon      (lon) float64 1.25 3.75 6.25 8.75 11.25 ... 351.2 353.8 356.2 358.8</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'pr'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 144</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-fc852f1b-7d53-480a-89c1-c74914af3319' class='xr-array-in' type='checkbox' checked><label for='section-fc852f1b-7d53-480a-89c1-c74914af3319' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0</span></div><div class='xr-array-data'><pre>array([[0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       ...,\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-9191b231-6c73-4160-857e-d4609a35f0b8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9191b231-6c73-4160-857e-d4609a35f0b8' class='xr-section-summary' >Coordinates: <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 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'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-5f1892b1-cd38-47f1-ad76-07cf112adc9d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5f1892b1-cd38-47f1-ad76-07cf112adc9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a68088c-c39d-42dd-beb1-37ec5211f0bd' class='xr-var-data-in' type='checkbox'><label for='data-2a68088c-c39d-42dd-beb1-37ec5211f0bd' 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., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
+       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
+       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
+       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
+       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
+       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
+       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
+       "        79.,  81.,  83.,  85.,  87.,  89.])</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'>1.25 3.75 6.25 ... 356.2 358.8</div><input id='attrs-b73e3be8-52d8-4c0f-b1f4-417ce92d4746' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b73e3be8-52d8-4c0f-b1f4-417ce92d4746' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a2a079f-defb-4605-9a30-10f530d47045' class='xr-var-data-in' type='checkbox'><label for='data-1a2a079f-defb-4605-9a30-10f530d47045' 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([  1.25,   3.75,   6.25,   8.75,  11.25,  13.75,  16.25,  18.75,  21.25,\n",
+       "        23.75,  26.25,  28.75,  31.25,  33.75,  36.25,  38.75,  41.25,  43.75,\n",
+       "        46.25,  48.75,  51.25,  53.75,  56.25,  58.75,  61.25,  63.75,  66.25,\n",
+       "        68.75,  71.25,  73.75,  76.25,  78.75,  81.25,  83.75,  86.25,  88.75,\n",
+       "        91.25,  93.75,  96.25,  98.75, 101.25, 103.75, 106.25, 108.75, 111.25,\n",
+       "       113.75, 116.25, 118.75, 121.25, 123.75, 126.25, 128.75, 131.25, 133.75,\n",
+       "       136.25, 138.75, 141.25, 143.75, 146.25, 148.75, 151.25, 153.75, 156.25,\n",
+       "       158.75, 161.25, 163.75, 166.25, 168.75, 171.25, 173.75, 176.25, 178.75,\n",
+       "       181.25, 183.75, 186.25, 188.75, 191.25, 193.75, 196.25, 198.75, 201.25,\n",
+       "       203.75, 206.25, 208.75, 211.25, 213.75, 216.25, 218.75, 221.25, 223.75,\n",
+       "       226.25, 228.75, 231.25, 233.75, 236.25, 238.75, 241.25, 243.75, 246.25,\n",
+       "       248.75, 251.25, 253.75, 256.25, 258.75, 261.25, 263.75, 266.25, 268.75,\n",
+       "       271.25, 273.75, 276.25, 278.75, 281.25, 283.75, 286.25, 288.75, 291.25,\n",
+       "       293.75, 296.25, 298.75, 301.25, 303.75, 306.25, 308.75, 311.25, 313.75,\n",
+       "       316.25, 318.75, 321.25, 323.75, 326.25, 328.75, 331.25, 333.75, 336.25,\n",
+       "       338.75, 341.25, 343.75, 346.25, 348.75, 351.25, 353.75, 356.25, 358.75])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7abd48c5-1851-4cf0-96f8-d563c55d17c3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7abd48c5-1851-4cf0-96f8-d563c55d17c3' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'pr' (lat: 90, lon: 144)>\n",
+       "array([[0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       ...,\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)\n",
+       "Coordinates:\n",
+       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
+       "  * lon      (lon) float64 1.25 3.75 6.25 8.75 11.25 ... 351.2 353.8 356.2 358.8"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_day.pr[0] - ds.pr[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "878b6b6a-7651-47cf-9618-ae50dfc15e2c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x1641e1190>"
+      ]
+     },
+     "execution_count": 20,
+     "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": [
+    "(ds_gra_day.pr[-1]-ds.pr[-1]).plot()  # Just checking there ARE same"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e33efc59-649c-4632-b7ba-799043353387",
+   "metadata": {},
+   "source": [
+    "### 2.2 Month"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "1e36edc2-9d01-4881-963a-830859301123",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_gra_month = ds.temporal.group_average(\"pr\", freq=\"month\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "0086e66a-3cd9-4ebe-9d2f-36603d158409",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(72, 90, 144)"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_month.pr.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "2033f778-7196-482c-95ea-fbf8f7d97e68",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x1645f2670>"
+      ]
+     },
+     "execution_count": 23,
+     "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": [
+    "(ds_gra_month.pr[0]-ds.pr[0]).plot()  # Just checking there are NOT same"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6e4b95fb-49e7-4905-82ac-a174d2959d5d",
+   "metadata": {},
+   "source": [
+    "### 2.3 Year"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "477b1c69-08df-48c1-8e6b-77b13d707af1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_gra_year = ds.temporal.group_average(\"pr\", freq=\"year\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "8b199df6-0cbe-4b7d-a336-47628726ee34",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(6, 90, 144)"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_year.pr.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "89a13d86-e4d3-409f-b59a-6aeb685217e5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x163f5a760>"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "(ds_gra_month.pr[-1]-ds_gra_year.pr[-1]).plot()  # Just checking there are NOT same"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d9583dfb-285f-4bab-8bb7-bea6243af270",
+   "metadata": {},
+   "source": [
+    "### 2.4 Season"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "c478328f-63fd-4a5a-a323-bd3f54c8db24",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_gra_season = ds.temporal.group_average(\"pr\", freq=\"season\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "544c53e0-a676-431a-8a72-84b542ed2874",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(25, 90, 144)"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_season.pr.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "bdf17235-d9eb-450e-b14d-8a11655a9b2e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "  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:   (lat: 90, bnds: 2, lon: 144, time: 25)\n",
+       "Coordinates:\n",
+       "  * lat       (lat) float64 -89.0 -87.0 -85.0 -83.0 ... 83.0 85.0 87.0 89.0\n",
+       "  * lon       (lon) float64 1.25 3.75 6.25 8.75 ... 351.2 353.8 356.2 358.8\n",
+       "  * time      (time) datetime64[ns] 2000-01-01 2000-04-01 ... 2006-01-01\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    lat_bnds  (lat, bnds) float64 -90.0 -88.0 -88.0 -86.0 ... 88.0 88.0 90.0\n",
+       "    lon_bnds  (lon, bnds) float64 0.0 2.5 2.5 5.0 ... 355.0 357.5 357.5 360.0\n",
+       "    pr        (time, lat, lon) float32 1.85e-06 1.85e-06 ... 1.717e-06 1.717e-06\n",
+       "Attributes: (12/27)\n",
+       "    institution:            NASA/GISS (Goddard Institute for Space Studies) N...\n",
+       "    institute_id:           NASA-GISS\n",
+       "    experiment_id:          historical\n",
+       "    source:                 GISS-E2-H-Eh135f9f Atmosphere: GISS-E2; Ocean: H\n",
+       "    model_id:               GISS-E2-H\n",
+       "    forcing:                GHG, LU, Sl, Vl, BC, OC, SA, Oz (also includes BC...\n",
+       "    ...                     ...\n",
+       "    table_id:               Table day (27 April 2011) 86d1558d99b6ed1e7a886ab...\n",
+       "    title:                  GISS-E2-H model output prepared for CMIP5 historical\n",
+       "    parent_experiment:      pre-industrial control\n",
+       "    modeling_realm:         atmos\n",
+       "    realization:            6\n",
+       "    cmor_version:           2.5.7</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-bd6993ee-3bdc-4d60-a21c-37d0be61371c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bd6993ee-3bdc-4d60-a21c-37d0be61371c' 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'>lat</span>: 90</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lon</span>: 144</li><li><span class='xr-has-index'>time</span>: 25</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-26b94ad4-bbbe-4e67-9f48-700cfa36fe41' class='xr-section-summary-in' type='checkbox'  checked><label for='section-26b94ad4-bbbe-4e67-9f48-700cfa36fe41' 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'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-9c205dec-ecd2-4ea2-b476-37658ab5e1ad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c205dec-ecd2-4ea2-b476-37658ab5e1ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0cba6c7b-93f7-4e93-a864-9ec68fcd736b' class='xr-var-data-in' type='checkbox'><label for='data-0cba6c7b-93f7-4e93-a864-9ec68fcd736b' 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., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
+       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
+       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
+       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
+       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
+       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
+       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
+       "        79.,  81.,  83.,  85.,  87.,  89.])</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'>1.25 3.75 6.25 ... 356.2 358.8</div><input id='attrs-c2e459ce-30cb-4ca2-af81-9e5ffa65ba84' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c2e459ce-30cb-4ca2-af81-9e5ffa65ba84' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d2d36e5-dc34-4f4d-b67e-1cf27e8d1b68' class='xr-var-data-in' type='checkbox'><label for='data-6d2d36e5-dc34-4f4d-b67e-1cf27e8d1b68' 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([  1.25,   3.75,   6.25,   8.75,  11.25,  13.75,  16.25,  18.75,  21.25,\n",
+       "        23.75,  26.25,  28.75,  31.25,  33.75,  36.25,  38.75,  41.25,  43.75,\n",
+       "        46.25,  48.75,  51.25,  53.75,  56.25,  58.75,  61.25,  63.75,  66.25,\n",
+       "        68.75,  71.25,  73.75,  76.25,  78.75,  81.25,  83.75,  86.25,  88.75,\n",
+       "        91.25,  93.75,  96.25,  98.75, 101.25, 103.75, 106.25, 108.75, 111.25,\n",
+       "       113.75, 116.25, 118.75, 121.25, 123.75, 126.25, 128.75, 131.25, 133.75,\n",
+       "       136.25, 138.75, 141.25, 143.75, 146.25, 148.75, 151.25, 153.75, 156.25,\n",
+       "       158.75, 161.25, 163.75, 166.25, 168.75, 171.25, 173.75, 176.25, 178.75,\n",
+       "       181.25, 183.75, 186.25, 188.75, 191.25, 193.75, 196.25, 198.75, 201.25,\n",
+       "       203.75, 206.25, 208.75, 211.25, 213.75, 216.25, 218.75, 221.25, 223.75,\n",
+       "       226.25, 228.75, 231.25, 233.75, 236.25, 238.75, 241.25, 243.75, 246.25,\n",
+       "       248.75, 251.25, 253.75, 256.25, 258.75, 261.25, 263.75, 266.25, 268.75,\n",
+       "       271.25, 273.75, 276.25, 278.75, 281.25, 283.75, 286.25, 288.75, 291.25,\n",
+       "       293.75, 296.25, 298.75, 301.25, 303.75, 306.25, 308.75, 311.25, 313.75,\n",
+       "       316.25, 318.75, 321.25, 323.75, 326.25, 328.75, 331.25, 333.75, 336.25,\n",
+       "       338.75, 341.25, 343.75, 346.25, 348.75, 351.25, 353.75, 356.25, 358.75])</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'>2000-01-01 ... 2006-01-01</div><input id='attrs-c8b6037a-17d8-40e1-a74a-44b570fdc3bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c8b6037a-17d8-40e1-a74a-44b570fdc3bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f342d705-d5b8-4db2-8c4c-31a8a163eaad' class='xr-var-data-in' type='checkbox'><label for='data-f342d705-d5b8-4db2-8c4c-31a8a163eaad' 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;2000-01-01T00:00:00.000000000&#x27;, &#x27;2000-04-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2000-07-01T00:00:00.000000000&#x27;, &#x27;2000-10-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2001-01-01T00:00:00.000000000&#x27;, &#x27;2001-04-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2001-07-01T00:00:00.000000000&#x27;, &#x27;2001-10-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2002-01-01T00:00:00.000000000&#x27;, &#x27;2002-04-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2002-07-01T00:00:00.000000000&#x27;, &#x27;2002-10-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2003-01-01T00:00:00.000000000&#x27;, &#x27;2003-04-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2003-07-01T00:00:00.000000000&#x27;, &#x27;2003-10-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2004-01-01T00:00:00.000000000&#x27;, &#x27;2004-04-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2004-07-01T00:00:00.000000000&#x27;, &#x27;2004-10-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2005-01-01T00:00:00.000000000&#x27;, &#x27;2005-04-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2005-07-01T00:00:00.000000000&#x27;, &#x27;2005-10-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2006-01-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7d02d5a3-d169-41c5-b1a5-c7d5bfaa8b72' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7d02d5a3-d169-41c5-b1a5-c7d5bfaa8b72' class='xr-section-summary' >Data variables: <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>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'>...</div><input id='attrs-649b16ed-12f6-4b74-87d2-e00c83a38751' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-649b16ed-12f6-4b74-87d2-e00c83a38751' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-630ec6dd-eb65-4379-a674-6e8001830ae5' class='xr-var-data-in' type='checkbox'><label for='data-630ec6dd-eb65-4379-a674-6e8001830ae5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-90., -88.],\n",
+       "       [-88., -86.],\n",
+       "       [-86., -84.],\n",
+       "       [-84., -82.],\n",
+       "       [-82., -80.],\n",
+       "       [-80., -78.],\n",
+       "       [-78., -76.],\n",
+       "       [-76., -74.],\n",
+       "       [-74., -72.],\n",
+       "       [-72., -70.],\n",
+       "       [-70., -68.],\n",
+       "       [-68., -66.],\n",
+       "       [-66., -64.],\n",
+       "       [-64., -62.],\n",
+       "       [-62., -60.],\n",
+       "       [-60., -58.],\n",
+       "       [-58., -56.],\n",
+       "       [-56., -54.],\n",
+       "       [-54., -52.],\n",
+       "       [-52., -50.],\n",
+       "       [-50., -48.],\n",
+       "       [-48., -46.],\n",
+       "       [-46., -44.],\n",
+       "       [-44., -42.],\n",
+       "       [-42., -40.],\n",
+       "       [-40., -38.],\n",
+       "       [-38., -36.],\n",
+       "       [-36., -34.],\n",
+       "       [-34., -32.],\n",
+       "       [-32., -30.],\n",
+       "       [-30., -28.],\n",
+       "       [-28., -26.],\n",
+       "       [-26., -24.],\n",
+       "       [-24., -22.],\n",
+       "       [-22., -20.],\n",
+       "       [-20., -18.],\n",
+       "       [-18., -16.],\n",
+       "       [-16., -14.],\n",
+       "       [-14., -12.],\n",
+       "       [-12., -10.],\n",
+       "       [-10.,  -8.],\n",
+       "       [ -8.,  -6.],\n",
+       "       [ -6.,  -4.],\n",
+       "       [ -4.,  -2.],\n",
+       "       [ -2.,   0.],\n",
+       "       [  0.,   2.],\n",
+       "       [  2.,   4.],\n",
+       "       [  4.,   6.],\n",
+       "       [  6.,   8.],\n",
+       "       [  8.,  10.],\n",
+       "       [ 10.,  12.],\n",
+       "       [ 12.,  14.],\n",
+       "       [ 14.,  16.],\n",
+       "       [ 16.,  18.],\n",
+       "       [ 18.,  20.],\n",
+       "       [ 20.,  22.],\n",
+       "       [ 22.,  24.],\n",
+       "       [ 24.,  26.],\n",
+       "       [ 26.,  28.],\n",
+       "       [ 28.,  30.],\n",
+       "       [ 30.,  32.],\n",
+       "       [ 32.,  34.],\n",
+       "       [ 34.,  36.],\n",
+       "       [ 36.,  38.],\n",
+       "       [ 38.,  40.],\n",
+       "       [ 40.,  42.],\n",
+       "       [ 42.,  44.],\n",
+       "       [ 44.,  46.],\n",
+       "       [ 46.,  48.],\n",
+       "       [ 48.,  50.],\n",
+       "       [ 50.,  52.],\n",
+       "       [ 52.,  54.],\n",
+       "       [ 54.,  56.],\n",
+       "       [ 56.,  58.],\n",
+       "       [ 58.,  60.],\n",
+       "       [ 60.,  62.],\n",
+       "       [ 62.,  64.],\n",
+       "       [ 64.,  66.],\n",
+       "       [ 66.,  68.],\n",
+       "       [ 68.,  70.],\n",
+       "       [ 70.,  72.],\n",
+       "       [ 72.,  74.],\n",
+       "       [ 74.,  76.],\n",
+       "       [ 76.,  78.],\n",
+       "       [ 78.,  80.],\n",
+       "       [ 80.,  82.],\n",
+       "       [ 82.,  84.],\n",
+       "       [ 84.,  86.],\n",
+       "       [ 86.,  88.],\n",
+       "       [ 88.,  90.]])</pre></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'>...</div><input id='attrs-05c2bc14-dc9b-46bc-b21c-398a72edfb93' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-05c2bc14-dc9b-46bc-b21c-398a72edfb93' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0c6096d-c720-4aa2-804f-52841d1c6924' class='xr-var-data-in' type='checkbox'><label for='data-c0c6096d-c720-4aa2-804f-52841d1c6924' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  0. ,   2.5],\n",
+       "       [  2.5,   5. ],\n",
+       "       [  5. ,   7.5],\n",
+       "       ...,\n",
+       "       [352.5, 355. ],\n",
+       "       [355. , 357.5],\n",
+       "       [357.5, 360. ]])</pre></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'>1.85e-06 1.85e-06 ... 1.717e-06</div><input id='attrs-1b43c9c0-7750-416b-b41f-a3a878f6f58f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b43c9c0-7750-416b-b41f-a3a878f6f58f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2a4c2a1-d4ba-494e-b97c-5e2064ba802f' class='xr-var-data-in' type='checkbox'><label for='data-d2a4c2a1-d4ba-494e-b97c-5e2064ba802f' 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>operation :</span></dt><dd>temporal_avg</dd><dt><span>mode :</span></dt><dd>group_average</dd><dt><span>freq :</span></dt><dd>season</dd><dt><span>weighted :</span></dt><dd>True</dd><dt><span>center_times :</span></dt><dd>False</dd><dt><span>dec_mode :</span></dt><dd>DJF</dd><dt><span>drop_incomplete_djf :</span></dt><dd>False</dd></dl></div><div class='xr-var-data'><pre>array([[[1.85024521e-06, 1.85024521e-06, 1.85024521e-06, ...,\n",
+       "         1.85024521e-06, 1.85024521e-06, 1.85024521e-06],\n",
+       "        [3.82354438e-06, 4.01808393e-06, 4.29359443e-06, ...,\n",
+       "         3.98480233e-06, 3.97140184e-06, 3.84026225e-06],\n",
+       "        [3.92451784e-06, 3.52330380e-06, 3.25742144e-06, ...,\n",
+       "         6.36785580e-06, 5.46364527e-06, 4.58668228e-06],\n",
+       "        ...,\n",
+       "        [5.91683465e-06, 6.39784776e-06, 6.72323858e-06, ...,\n",
+       "         4.77793765e-06, 5.19164723e-06, 5.63094409e-06],\n",
+       "        [4.80026210e-06, 4.66889378e-06, 4.61527225e-06, ...,\n",
+       "         4.16468538e-06, 4.42129340e-06, 4.67891005e-06],\n",
+       "        [2.27408441e-06, 2.27408441e-06, 2.27408441e-06, ...,\n",
+       "         2.27408441e-06, 2.27408441e-06, 2.27408441e-06]],\n",
+       "\n",
+       "       [[6.25496568e-07, 6.25496568e-07, 6.25496568e-07, ...,\n",
+       "         6.25496568e-07, 6.25496568e-07, 6.25496568e-07],\n",
+       "        [9.92164246e-07, 1.08661379e-06, 1.16988303e-06, ...,\n",
+       "         9.44357055e-07, 9.32133673e-07, 9.13008307e-07],\n",
+       "        [2.15364707e-06, 1.94613631e-06, 1.72529326e-06, ...,\n",
+       "         2.83860118e-06, 2.57158308e-06, 2.40329064e-06],\n",
+       "...\n",
+       "        [8.19568686e-06, 8.07490051e-06, 7.89476326e-06, ...,\n",
+       "         8.70716030e-06, 7.91202092e-06, 8.42508507e-06],\n",
+       "        [8.83597386e-06, 8.54288101e-06, 9.20794901e-06, ...,\n",
+       "         8.06326352e-06, 8.34923594e-06, 8.22033508e-06],\n",
+       "        [3.98521115e-06, 3.98521115e-06, 3.98521115e-06, ...,\n",
+       "         3.98521115e-06, 3.98521115e-06, 3.98521115e-06]],\n",
+       "\n",
+       "       [[1.71692784e-06, 1.71692784e-06, 1.71692784e-06, ...,\n",
+       "         1.71692784e-06, 1.71692784e-06, 1.71692784e-06],\n",
+       "        [2.48149354e-06, 2.49271670e-06, 2.59565104e-06, ...,\n",
+       "         3.18132788e-06, 3.08520771e-06, 2.79807864e-06],\n",
+       "        [3.58099533e-06, 2.88810679e-06, 2.56785393e-06, ...,\n",
+       "         6.46176886e-06, 5.41026702e-06, 4.49872368e-06],\n",
+       "        ...,\n",
+       "        [4.22426046e-06, 4.27413124e-06, 4.01923899e-06, ...,\n",
+       "         4.92412073e-06, 4.33966716e-06, 4.64226696e-06],\n",
+       "        [4.15941031e-06, 3.56836631e-06, 4.04928915e-06, ...,\n",
+       "         3.49455149e-06, 3.53633231e-06, 3.67595089e-06],\n",
+       "        [1.71728595e-06, 1.71728595e-06, 1.71728595e-06, ...,\n",
+       "         1.71728595e-06, 1.71728595e-06, 1.71728595e-06]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fb30d447-f9dc-4eab-962e-a4f1abfdf715' class='xr-section-summary-in' type='checkbox'  ><label for='section-fb30d447-f9dc-4eab-962e-a4f1abfdf715' class='xr-section-summary' >Attributes: <span>(27)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>institution :</span></dt><dd>NASA/GISS (Goddard Institute for Space Studies) New York, NY</dd><dt><span>institute_id :</span></dt><dd>NASA-GISS</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>source :</span></dt><dd>GISS-E2-H-Eh135f9f Atmosphere: GISS-E2; Ocean: H</dd><dt><span>model_id :</span></dt><dd>GISS-E2-H</dd><dt><span>forcing :</span></dt><dd>GHG, LU, Sl, Vl, BC, OC, SA, Oz (also includes BC on snow - Nitrate aerosols)</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p1</dd><dt><span>branch_time :</span></dt><dd>2510.0</dd><dt><span>contact :</span></dt><dd>Kenneth Lo (cdkkl@giss.nasa.gov)</dd><dt><span>references :</span></dt><dd>http://data.giss.nasa.gov/modelE/ar5</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>b31006b5-e988-4b70-8908-858a18cfa2bb</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>day</dd><dt><span>creation_date :</span></dt><dd>2013-04-18T19:18:11Z</dd><dt><span>history :</span></dt><dd>2013-04-18T19:18:11Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table day (27 April 2011) 86d1558d99b6ed1e7a886ab3fd717b58</dd><dt><span>title :</span></dt><dd>GISS-E2-H model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>6</dd><dt><span>cmor_version :</span></dt><dd>2.5.7</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:   (lat: 90, bnds: 2, lon: 144, time: 25)\n",
+       "Coordinates:\n",
+       "  * lat       (lat) float64 -89.0 -87.0 -85.0 -83.0 ... 83.0 85.0 87.0 89.0\n",
+       "  * lon       (lon) float64 1.25 3.75 6.25 8.75 ... 351.2 353.8 356.2 358.8\n",
+       "  * time      (time) datetime64[ns] 2000-01-01 2000-04-01 ... 2006-01-01\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    lat_bnds  (lat, bnds) float64 ...\n",
+       "    lon_bnds  (lon, bnds) float64 ...\n",
+       "    pr        (time, lat, lon) float32 1.85e-06 1.85e-06 ... 1.717e-06 1.717e-06\n",
+       "Attributes: (12/27)\n",
+       "    institution:            NASA/GISS (Goddard Institute for Space Studies) N...\n",
+       "    institute_id:           NASA-GISS\n",
+       "    experiment_id:          historical\n",
+       "    source:                 GISS-E2-H-Eh135f9f Atmosphere: GISS-E2; Ocean: H\n",
+       "    model_id:               GISS-E2-H\n",
+       "    forcing:                GHG, LU, Sl, Vl, BC, OC, SA, Oz (also includes BC...\n",
+       "    ...                     ...\n",
+       "    table_id:               Table day (27 April 2011) 86d1558d99b6ed1e7a886ab...\n",
+       "    title:                  GISS-E2-H model output prepared for CMIP5 historical\n",
+       "    parent_experiment:      pre-industrial control\n",
+       "    modeling_realm:         atmos\n",
+       "    realization:            6\n",
+       "    cmor_version:           2.5.7"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_season"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "e6f45b58-4a2b-4142-9d4c-49bf2525cb67",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "season_config_dict = {\"dec_mode\": \"DJF\", \"drop_incomplete_djf\": True}\n",
+    "ds_gra_season2 = ds.temporal.group_average(\"pr\", freq=\"season\", season_config=season_config_dict)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "1eca45d6-04a4-40c5-9d52-0c0adaebfb59",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(25, 90, 144)"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_season2.pr.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "466297d4-4276-4a2e-b17c-c6d158624f52",
+   "metadata": {},
+   "outputs": [
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+       ".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:   (lat: 90, lon: 144, bnds: 2, time: 25)\n",
+       "Coordinates:\n",
+       "  * lat       (lat) float64 -89.0 -87.0 -85.0 -83.0 ... 83.0 85.0 87.0 89.0\n",
+       "  * lon       (lon) float64 1.25 3.75 6.25 8.75 ... 351.2 353.8 356.2 358.8\n",
+       "  * time      (time) datetime64[ns] 2000-01-01 2000-04-01 ... 2006-01-01\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    lat_bnds  (lat, bnds) float64 -90.0 -88.0 -88.0 -86.0 ... 88.0 88.0 90.0\n",
+       "    lon_bnds  (lon, bnds) float64 0.0 2.5 2.5 5.0 ... 355.0 357.5 357.5 360.0\n",
+       "    pr        (time, lat, lon) float32 1.858e-06 1.858e-06 ... 1.727e-06\n",
+       "Attributes: (12/27)\n",
+       "    institution:            NASA/GISS (Goddard Institute for Space Studies) N...\n",
+       "    institute_id:           NASA-GISS\n",
+       "    experiment_id:          historical\n",
+       "    source:                 GISS-E2-H-Eh135f9f Atmosphere: GISS-E2; Ocean: H\n",
+       "    model_id:               GISS-E2-H\n",
+       "    forcing:                GHG, LU, Sl, Vl, BC, OC, SA, Oz (also includes BC...\n",
+       "    ...                     ...\n",
+       "    table_id:               Table day (27 April 2011) 86d1558d99b6ed1e7a886ab...\n",
+       "    title:                  GISS-E2-H model output prepared for CMIP5 historical\n",
+       "    parent_experiment:      pre-industrial control\n",
+       "    modeling_realm:         atmos\n",
+       "    realization:            6\n",
+       "    cmor_version:           2.5.7</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-ae65f343-00b6-45a6-9856-c0ebc7065cfc' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ae65f343-00b6-45a6-9856-c0ebc7065cfc' 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'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 144</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>time</span>: 25</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-469566b7-0665-4b13-ab38-880287f05cec' class='xr-section-summary-in' type='checkbox'  checked><label for='section-469566b7-0665-4b13-ab38-880287f05cec' 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'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-4f5e60fa-2137-4778-b07b-a1582abed5dc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f5e60fa-2137-4778-b07b-a1582abed5dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1dd80c0-918c-4051-a70d-9ef624a04485' class='xr-var-data-in' type='checkbox'><label for='data-f1dd80c0-918c-4051-a70d-9ef624a04485' 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., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
+       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
+       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
+       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
+       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
+       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
+       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
+       "        79.,  81.,  83.,  85.,  87.,  89.])</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'>1.25 3.75 6.25 ... 356.2 358.8</div><input id='attrs-1f97234b-b349-48d7-b564-4723bde3aa55' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f97234b-b349-48d7-b564-4723bde3aa55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13c19b0b-50f7-4a51-b1e6-142c05efaea5' class='xr-var-data-in' type='checkbox'><label for='data-13c19b0b-50f7-4a51-b1e6-142c05efaea5' 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([  1.25,   3.75,   6.25,   8.75,  11.25,  13.75,  16.25,  18.75,  21.25,\n",
+       "        23.75,  26.25,  28.75,  31.25,  33.75,  36.25,  38.75,  41.25,  43.75,\n",
+       "        46.25,  48.75,  51.25,  53.75,  56.25,  58.75,  61.25,  63.75,  66.25,\n",
+       "        68.75,  71.25,  73.75,  76.25,  78.75,  81.25,  83.75,  86.25,  88.75,\n",
+       "        91.25,  93.75,  96.25,  98.75, 101.25, 103.75, 106.25, 108.75, 111.25,\n",
+       "       113.75, 116.25, 118.75, 121.25, 123.75, 126.25, 128.75, 131.25, 133.75,\n",
+       "       136.25, 138.75, 141.25, 143.75, 146.25, 148.75, 151.25, 153.75, 156.25,\n",
+       "       158.75, 161.25, 163.75, 166.25, 168.75, 171.25, 173.75, 176.25, 178.75,\n",
+       "       181.25, 183.75, 186.25, 188.75, 191.25, 193.75, 196.25, 198.75, 201.25,\n",
+       "       203.75, 206.25, 208.75, 211.25, 213.75, 216.25, 218.75, 221.25, 223.75,\n",
+       "       226.25, 228.75, 231.25, 233.75, 236.25, 238.75, 241.25, 243.75, 246.25,\n",
+       "       248.75, 251.25, 253.75, 256.25, 258.75, 261.25, 263.75, 266.25, 268.75,\n",
+       "       271.25, 273.75, 276.25, 278.75, 281.25, 283.75, 286.25, 288.75, 291.25,\n",
+       "       293.75, 296.25, 298.75, 301.25, 303.75, 306.25, 308.75, 311.25, 313.75,\n",
+       "       316.25, 318.75, 321.25, 323.75, 326.25, 328.75, 331.25, 333.75, 336.25,\n",
+       "       338.75, 341.25, 343.75, 346.25, 348.75, 351.25, 353.75, 356.25, 358.75])</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'>2000-01-01 ... 2006-01-01</div><input id='attrs-92f32822-77ab-4ecc-847f-c9ec3b71a7ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-92f32822-77ab-4ecc-847f-c9ec3b71a7ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13952536-439d-46c5-a8ca-960056b86ec7' class='xr-var-data-in' type='checkbox'><label for='data-13952536-439d-46c5-a8ca-960056b86ec7' 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;2000-01-01T00:00:00.000000000&#x27;, &#x27;2000-04-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2000-07-01T00:00:00.000000000&#x27;, &#x27;2000-10-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2001-01-01T00:00:00.000000000&#x27;, &#x27;2001-04-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2001-07-01T00:00:00.000000000&#x27;, &#x27;2001-10-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2002-01-01T00:00:00.000000000&#x27;, &#x27;2002-04-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2002-07-01T00:00:00.000000000&#x27;, &#x27;2002-10-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2003-01-01T00:00:00.000000000&#x27;, &#x27;2003-04-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2003-07-01T00:00:00.000000000&#x27;, &#x27;2003-10-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2004-01-01T00:00:00.000000000&#x27;, &#x27;2004-04-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2004-07-01T00:00:00.000000000&#x27;, &#x27;2004-10-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2005-01-01T00:00:00.000000000&#x27;, &#x27;2005-04-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2005-07-01T00:00:00.000000000&#x27;, &#x27;2005-10-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2006-01-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e228e0da-2589-43be-b9dd-838f463e20c9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e228e0da-2589-43be-b9dd-838f463e20c9' class='xr-section-summary' >Data variables: <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>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'>...</div><input id='attrs-795218e9-e0c2-4e7e-ba40-0184ed642a34' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-795218e9-e0c2-4e7e-ba40-0184ed642a34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5180e42-5e63-49bf-95f0-c088d229bd64' class='xr-var-data-in' type='checkbox'><label for='data-d5180e42-5e63-49bf-95f0-c088d229bd64' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-90., -88.],\n",
+       "       [-88., -86.],\n",
+       "       [-86., -84.],\n",
+       "       [-84., -82.],\n",
+       "       [-82., -80.],\n",
+       "       [-80., -78.],\n",
+       "       [-78., -76.],\n",
+       "       [-76., -74.],\n",
+       "       [-74., -72.],\n",
+       "       [-72., -70.],\n",
+       "       [-70., -68.],\n",
+       "       [-68., -66.],\n",
+       "       [-66., -64.],\n",
+       "       [-64., -62.],\n",
+       "       [-62., -60.],\n",
+       "       [-60., -58.],\n",
+       "       [-58., -56.],\n",
+       "       [-56., -54.],\n",
+       "       [-54., -52.],\n",
+       "       [-52., -50.],\n",
+       "       [-50., -48.],\n",
+       "       [-48., -46.],\n",
+       "       [-46., -44.],\n",
+       "       [-44., -42.],\n",
+       "       [-42., -40.],\n",
+       "       [-40., -38.],\n",
+       "       [-38., -36.],\n",
+       "       [-36., -34.],\n",
+       "       [-34., -32.],\n",
+       "       [-32., -30.],\n",
+       "       [-30., -28.],\n",
+       "       [-28., -26.],\n",
+       "       [-26., -24.],\n",
+       "       [-24., -22.],\n",
+       "       [-22., -20.],\n",
+       "       [-20., -18.],\n",
+       "       [-18., -16.],\n",
+       "       [-16., -14.],\n",
+       "       [-14., -12.],\n",
+       "       [-12., -10.],\n",
+       "       [-10.,  -8.],\n",
+       "       [ -8.,  -6.],\n",
+       "       [ -6.,  -4.],\n",
+       "       [ -4.,  -2.],\n",
+       "       [ -2.,   0.],\n",
+       "       [  0.,   2.],\n",
+       "       [  2.,   4.],\n",
+       "       [  4.,   6.],\n",
+       "       [  6.,   8.],\n",
+       "       [  8.,  10.],\n",
+       "       [ 10.,  12.],\n",
+       "       [ 12.,  14.],\n",
+       "       [ 14.,  16.],\n",
+       "       [ 16.,  18.],\n",
+       "       [ 18.,  20.],\n",
+       "       [ 20.,  22.],\n",
+       "       [ 22.,  24.],\n",
+       "       [ 24.,  26.],\n",
+       "       [ 26.,  28.],\n",
+       "       [ 28.,  30.],\n",
+       "       [ 30.,  32.],\n",
+       "       [ 32.,  34.],\n",
+       "       [ 34.,  36.],\n",
+       "       [ 36.,  38.],\n",
+       "       [ 38.,  40.],\n",
+       "       [ 40.,  42.],\n",
+       "       [ 42.,  44.],\n",
+       "       [ 44.,  46.],\n",
+       "       [ 46.,  48.],\n",
+       "       [ 48.,  50.],\n",
+       "       [ 50.,  52.],\n",
+       "       [ 52.,  54.],\n",
+       "       [ 54.,  56.],\n",
+       "       [ 56.,  58.],\n",
+       "       [ 58.,  60.],\n",
+       "       [ 60.,  62.],\n",
+       "       [ 62.,  64.],\n",
+       "       [ 64.,  66.],\n",
+       "       [ 66.,  68.],\n",
+       "       [ 68.,  70.],\n",
+       "       [ 70.,  72.],\n",
+       "       [ 72.,  74.],\n",
+       "       [ 74.,  76.],\n",
+       "       [ 76.,  78.],\n",
+       "       [ 78.,  80.],\n",
+       "       [ 80.,  82.],\n",
+       "       [ 82.,  84.],\n",
+       "       [ 84.,  86.],\n",
+       "       [ 86.,  88.],\n",
+       "       [ 88.,  90.]])</pre></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'>...</div><input id='attrs-4a852283-6364-495a-a67d-c4ce423f4a93' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4a852283-6364-495a-a67d-c4ce423f4a93' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e3357c6-3041-40d3-adc9-cc51d785ca3f' class='xr-var-data-in' type='checkbox'><label for='data-8e3357c6-3041-40d3-adc9-cc51d785ca3f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  0. ,   2.5],\n",
+       "       [  2.5,   5. ],\n",
+       "       [  5. ,   7.5],\n",
+       "       ...,\n",
+       "       [352.5, 355. ],\n",
+       "       [355. , 357.5],\n",
+       "       [357.5, 360. ]])</pre></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'>1.858e-06 1.858e-06 ... 1.727e-06</div><input id='attrs-563df73a-ebfd-4e4c-9baf-15a21a99f901' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-563df73a-ebfd-4e4c-9baf-15a21a99f901' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-36517a8c-4b3b-49f0-be30-e85fe77b1d59' class='xr-var-data-in' type='checkbox'><label for='data-36517a8c-4b3b-49f0-be30-e85fe77b1d59' 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>operation :</span></dt><dd>temporal_avg</dd><dt><span>mode :</span></dt><dd>group_average</dd><dt><span>freq :</span></dt><dd>season</dd><dt><span>weighted :</span></dt><dd>True</dd><dt><span>center_times :</span></dt><dd>False</dd><dt><span>dec_mode :</span></dt><dd>DJF</dd><dt><span>drop_incomplete_djf :</span></dt><dd>True</dd></dl></div><div class='xr-var-data'><pre>array([[[1.85782085e-06, 1.85782085e-06, 1.85782085e-06, ...,\n",
+       "         1.85782085e-06, 1.85782085e-06, 1.85782085e-06],\n",
+       "        [3.90562809e-06, 4.10877146e-06, 4.38704319e-06, ...,\n",
+       "         4.08387768e-06, 4.05812307e-06, 3.91609319e-06],\n",
+       "        [4.00014915e-06, 3.58552256e-06, 3.27698103e-06, ...,\n",
+       "         6.53582902e-06, 5.60391254e-06, 4.70410941e-06],\n",
+       "        ...,\n",
+       "        [5.86005581e-06, 6.34318803e-06, 6.63115270e-06, ...,\n",
+       "         4.72195234e-06, 5.16692262e-06, 5.60470062e-06],\n",
+       "        [4.86819090e-06, 4.74157059e-06, 4.69330507e-06, ...,\n",
+       "         4.20752485e-06, 4.47287994e-06, 4.73876071e-06],\n",
+       "        [2.28055683e-06, 2.28055683e-06, 2.28055683e-06, ...,\n",
+       "         2.28055683e-06, 2.28055683e-06, 2.28055683e-06]],\n",
+       "\n",
+       "       [[6.25496568e-07, 6.25496568e-07, 6.25496568e-07, ...,\n",
+       "         6.25496568e-07, 6.25496568e-07, 6.25496568e-07],\n",
+       "        [9.92164246e-07, 1.08661379e-06, 1.16988303e-06, ...,\n",
+       "         9.44357055e-07, 9.32133673e-07, 9.13008307e-07],\n",
+       "        [2.15364707e-06, 1.94613631e-06, 1.72529326e-06, ...,\n",
+       "         2.83860118e-06, 2.57158308e-06, 2.40329064e-06],\n",
+       "...\n",
+       "        [8.19568686e-06, 8.07490051e-06, 7.89476326e-06, ...,\n",
+       "         8.70716030e-06, 7.91202092e-06, 8.42508507e-06],\n",
+       "        [8.83597386e-06, 8.54288101e-06, 9.20794901e-06, ...,\n",
+       "         8.06326352e-06, 8.34923594e-06, 8.22033508e-06],\n",
+       "        [3.98521115e-06, 3.98521115e-06, 3.98521115e-06, ...,\n",
+       "         3.98521115e-06, 3.98521115e-06, 3.98521115e-06]],\n",
+       "\n",
+       "       [[1.76386936e-06, 1.76386936e-06, 1.76386936e-06, ...,\n",
+       "         1.76386936e-06, 1.76386936e-06, 1.76386936e-06],\n",
+       "        [2.54761221e-06, 2.55307577e-06, 2.66065717e-06, ...,\n",
+       "         3.26458780e-06, 3.17934064e-06, 2.87691614e-06],\n",
+       "        [3.55880343e-06, 2.86119666e-06, 2.57539432e-06, ...,\n",
+       "         6.59468060e-06, 5.47082482e-06, 4.48443461e-06],\n",
+       "        ...,\n",
+       "        [4.29979082e-06, 4.35621087e-06, 4.09257018e-06, ...,\n",
+       "         5.02069042e-06, 4.42678356e-06, 4.73544742e-06],\n",
+       "        [4.25597273e-06, 3.64473749e-06, 4.13947737e-06, ...,\n",
+       "         3.56632381e-06, 3.61003845e-06, 3.74898741e-06],\n",
+       "        [1.72714215e-06, 1.72714215e-06, 1.72714215e-06, ...,\n",
+       "         1.72714215e-06, 1.72714215e-06, 1.72714215e-06]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ba8f22de-0f84-4aa6-a483-6b5eb399e90b' class='xr-section-summary-in' type='checkbox'  ><label for='section-ba8f22de-0f84-4aa6-a483-6b5eb399e90b' class='xr-section-summary' >Attributes: <span>(27)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>institution :</span></dt><dd>NASA/GISS (Goddard Institute for Space Studies) New York, NY</dd><dt><span>institute_id :</span></dt><dd>NASA-GISS</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>source :</span></dt><dd>GISS-E2-H-Eh135f9f Atmosphere: GISS-E2; Ocean: H</dd><dt><span>model_id :</span></dt><dd>GISS-E2-H</dd><dt><span>forcing :</span></dt><dd>GHG, LU, Sl, Vl, BC, OC, SA, Oz (also includes BC on snow - Nitrate aerosols)</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p1</dd><dt><span>branch_time :</span></dt><dd>2510.0</dd><dt><span>contact :</span></dt><dd>Kenneth Lo (cdkkl@giss.nasa.gov)</dd><dt><span>references :</span></dt><dd>http://data.giss.nasa.gov/modelE/ar5</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>b31006b5-e988-4b70-8908-858a18cfa2bb</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>day</dd><dt><span>creation_date :</span></dt><dd>2013-04-18T19:18:11Z</dd><dt><span>history :</span></dt><dd>2013-04-18T19:18:11Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table day (27 April 2011) 86d1558d99b6ed1e7a886ab3fd717b58</dd><dt><span>title :</span></dt><dd>GISS-E2-H model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>6</dd><dt><span>cmor_version :</span></dt><dd>2.5.7</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:   (lat: 90, lon: 144, bnds: 2, time: 25)\n",
+       "Coordinates:\n",
+       "  * lat       (lat) float64 -89.0 -87.0 -85.0 -83.0 ... 83.0 85.0 87.0 89.0\n",
+       "  * lon       (lon) float64 1.25 3.75 6.25 8.75 ... 351.2 353.8 356.2 358.8\n",
+       "  * time      (time) datetime64[ns] 2000-01-01 2000-04-01 ... 2006-01-01\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    lat_bnds  (lat, bnds) float64 ...\n",
+       "    lon_bnds  (lon, bnds) float64 ...\n",
+       "    pr        (time, lat, lon) float32 1.858e-06 1.858e-06 ... 1.727e-06\n",
+       "Attributes: (12/27)\n",
+       "    institution:            NASA/GISS (Goddard Institute for Space Studies) N...\n",
+       "    institute_id:           NASA-GISS\n",
+       "    experiment_id:          historical\n",
+       "    source:                 GISS-E2-H-Eh135f9f Atmosphere: GISS-E2; Ocean: H\n",
+       "    model_id:               GISS-E2-H\n",
+       "    forcing:                GHG, LU, Sl, Vl, BC, OC, SA, Oz (also includes BC...\n",
+       "    ...                     ...\n",
+       "    table_id:               Table day (27 April 2011) 86d1558d99b6ed1e7a886ab...\n",
+       "    title:                  GISS-E2-H model output prepared for CMIP5 historical\n",
+       "    parent_experiment:      pre-industrial control\n",
+       "    modeling_realm:         atmos\n",
+       "    realization:            6\n",
+       "    cmor_version:           2.5.7"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_season2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "a696b1c5-5a02-4e2e-80aa-66ba4f2f7a50",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x164524880>"
+      ]
+     },
+     "execution_count": 33,
+     "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": [
+    "(ds_gra_season.pr[-1]-ds_gra_season2.pr[-1]).plot()  # Just checking there are NOT same"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "95c405c5-10d9-4017-b2f6-86567eb50d8c",
+   "metadata": {},
+   "source": [
+    "### 2.5 Hour"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "2be8eafa-dd75-4a78-89f7-6792f8a13352",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_gra_hour = ds.temporal.group_average(\"pr\", freq=\"hour\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "6418c31e-e638-4536-b45d-5d7f32642ba9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(2190, 90, 144)"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_hour.pr.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "e47c850e-72f6-4eb0-8dd7-af5653ca4ffc",
+   "metadata": {},
+   "outputs": [
+    {
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+       "  stroke: currentColor;\n",
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+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (lat: 90, lon: 144)&gt;\n",
+       "array([[0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       ...,\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)\n",
+       "Coordinates:\n",
+       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
+       "  * lon      (lon) float64 1.25 3.75 6.25 8.75 11.25 ... 351.2 353.8 356.2 358.8</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'pr'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 144</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-fc21e1f3-21b5-4b09-a35f-29438ee7745a' class='xr-array-in' type='checkbox' checked><label for='section-fc21e1f3-21b5-4b09-a35f-29438ee7745a' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0</span></div><div class='xr-array-data'><pre>array([[0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       ...,\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-a0406ef6-9a58-4ab1-a35a-6f2456f55634' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a0406ef6-9a58-4ab1-a35a-6f2456f55634' class='xr-section-summary' >Coordinates: <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 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'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-8ddf0da7-0a74-45cf-bd40-2a234e07b449' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ddf0da7-0a74-45cf-bd40-2a234e07b449' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92fdc833-624d-456a-b612-b79d26863788' class='xr-var-data-in' type='checkbox'><label for='data-92fdc833-624d-456a-b612-b79d26863788' 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., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
+       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
+       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
+       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
+       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
+       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
+       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
+       "        79.,  81.,  83.,  85.,  87.,  89.])</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'>1.25 3.75 6.25 ... 356.2 358.8</div><input id='attrs-865cdd8b-0e2e-4f02-a7b5-ca085b4c7261' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-865cdd8b-0e2e-4f02-a7b5-ca085b4c7261' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2b704b2-4f02-4060-961c-d518aa3b7201' class='xr-var-data-in' type='checkbox'><label for='data-a2b704b2-4f02-4060-961c-d518aa3b7201' 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([  1.25,   3.75,   6.25,   8.75,  11.25,  13.75,  16.25,  18.75,  21.25,\n",
+       "        23.75,  26.25,  28.75,  31.25,  33.75,  36.25,  38.75,  41.25,  43.75,\n",
+       "        46.25,  48.75,  51.25,  53.75,  56.25,  58.75,  61.25,  63.75,  66.25,\n",
+       "        68.75,  71.25,  73.75,  76.25,  78.75,  81.25,  83.75,  86.25,  88.75,\n",
+       "        91.25,  93.75,  96.25,  98.75, 101.25, 103.75, 106.25, 108.75, 111.25,\n",
+       "       113.75, 116.25, 118.75, 121.25, 123.75, 126.25, 128.75, 131.25, 133.75,\n",
+       "       136.25, 138.75, 141.25, 143.75, 146.25, 148.75, 151.25, 153.75, 156.25,\n",
+       "       158.75, 161.25, 163.75, 166.25, 168.75, 171.25, 173.75, 176.25, 178.75,\n",
+       "       181.25, 183.75, 186.25, 188.75, 191.25, 193.75, 196.25, 198.75, 201.25,\n",
+       "       203.75, 206.25, 208.75, 211.25, 213.75, 216.25, 218.75, 221.25, 223.75,\n",
+       "       226.25, 228.75, 231.25, 233.75, 236.25, 238.75, 241.25, 243.75, 246.25,\n",
+       "       248.75, 251.25, 253.75, 256.25, 258.75, 261.25, 263.75, 266.25, 268.75,\n",
+       "       271.25, 273.75, 276.25, 278.75, 281.25, 283.75, 286.25, 288.75, 291.25,\n",
+       "       293.75, 296.25, 298.75, 301.25, 303.75, 306.25, 308.75, 311.25, 313.75,\n",
+       "       316.25, 318.75, 321.25, 323.75, 326.25, 328.75, 331.25, 333.75, 336.25,\n",
+       "       338.75, 341.25, 343.75, 346.25, 348.75, 351.25, 353.75, 356.25, 358.75])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c024b611-dee0-4785-84eb-b2ab8f18acd6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c024b611-dee0-4785-84eb-b2ab8f18acd6' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'pr' (lat: 90, lon: 144)>\n",
+       "array([[0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       ...,\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)\n",
+       "Coordinates:\n",
+       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
+       "  * lon      (lon) float64 1.25 3.75 6.25 8.75 11.25 ... 351.2 353.8 356.2 358.8"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_hour.pr[0] - ds.pr[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "c48c0ef6-3819-40fe-8cd0-d8df3b451827",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x1646fcf40>"
+      ]
+     },
+     "execution_count": 37,
+     "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": [
+    "(ds_gra_hour.pr[-1]-ds.pr[-1]).plot()  # Just checking there ARE same"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "90837e4d-80b9-4829-81dc-cc58fb995df2",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "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
+}
diff --git a/devel_test/temporal_average_monthly.ipynb b/devel_test/temporal_average_monthly.ipynb
new file mode 100644
index 0000000..3ddd11e
--- /dev/null
+++ b/devel_test/temporal_average_monthly.ipynb
@@ -0,0 +1,3584 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "ab1d3dea-b953-4e53-a94d-ab9a2d1ab39c",
+   "metadata": {},
+   "source": [
+    "# Temporal Average Testing\n",
+    "\n",
+    "Test procedure:\n",
+    "- XCDAT is source-installed from branch `feature/201-temporal-mean`\n",
+    "- PR: https://github.com/xCDAT/xcdat/pull/236\n",
+    "\n",
+    "## Load test data -- monthly, 1850-2005"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "ac226d47-9fdc-4f9c-b2ff-d9542b23c5f2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "a0ba4da0-603f-4437-ab82-7b3fa9a7c2d2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "demo_data_dir = '../tutorials/demo_data/CMIP5_demo_data'\n",
+    "demo_filename = 'ts_Amon_ACCESS1-0_historical_r1i1p1_185001-200512.nc'\n",
+    "demo_file = os.path.join(demo_data_dir, demo_filename)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "8a67df64-9f0b-4515-8fdc-2122a2eddd1c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import xcdat"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "c20b0719-f1a3-4781-a8af-465c05cf4240",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds = xcdat.open_dataset(demo_file)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "d965ac21-d875-4951-bb2d-70a6dedade3a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ts = ds.ts"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "1b9227cd-3c9a-4135-8228-b3b17eabe81c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
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+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
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+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
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+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
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+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
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+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
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+       "  display: contents;\n",
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+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
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+       "  grid-template-columns: 20px auto;\n",
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+       "\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",
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+       ".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",
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+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
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+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
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+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
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+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
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+       "\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",
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+       ".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",
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+       "  background-color: var(--xr-background-color-row-odd);\n",
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+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
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+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
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+       ".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",
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+       "  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.DataArray &#x27;ts&#x27; (time: 1872, lat: 145, lon: 192)&gt;\n",
+       "[52116480 values with dtype=float32]\n",
+       "Coordinates:\n",
+       "  * time     (time) datetime64[ns] 1850-01-16T12:00:00 ... 2005-12-16T12:00:00\n",
+       "  * lat      (lat) float64 -90.0 -88.75 -87.5 -86.25 ... 86.25 87.5 88.75 90.0\n",
+       "  * lon      (lon) float64 0.0 1.875 3.75 5.625 7.5 ... 352.5 354.4 356.2 358.1\n",
+       "Attributes:\n",
+       "    standard_name:     surface_temperature\n",
+       "    long_name:         Surface Temperature\n",
+       "    comment:           &quot;&quot;skin&quot;&quot; temperature (i.e., SST for open ocean)\n",
+       "    units:             K\n",
+       "    cell_methods:      time: mean\n",
+       "    cell_measures:     area: areacella\n",
+       "    history:           2012-01-17T03:16:09Z altered by CMOR: replaced missing...\n",
+       "    associated_files:  baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'ts'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1872</li><li><span class='xr-has-index'>lat</span>: 145</li><li><span class='xr-has-index'>lon</span>: 192</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-79a4a0b7-d654-448e-903a-b73e1cc18b5b' class='xr-array-in' type='checkbox' checked><label for='section-79a4a0b7-d654-448e-903a-b73e1cc18b5b' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[52116480 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-406fab4a-2f5b-43d7-89fd-3dff39ec2dd2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-406fab4a-2f5b-43d7-89fd-3dff39ec2dd2' 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'>1850-01-16T12:00:00 ... 2005-12-...</div><input id='attrs-070ec4c1-c56a-4b0d-848c-f1f2661352e4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-070ec4c1-c56a-4b0d-848c-f1f2661352e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b62839f7-f66e-43a1-a929-2b52e32876cf' class='xr-var-data-in' type='checkbox'><label for='data-b62839f7-f66e-43a1-a929-2b52e32876cf' 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;1850-01-16T12:00:00.000000000&#x27;, &#x27;1850-02-15T00:00:00.000000000&#x27;,\n",
+       "       &#x27;1850-03-16T12:00:00.000000000&#x27;, ..., &#x27;2005-10-16T12:00:00.000000000&#x27;,\n",
+       "       &#x27;2005-11-16T00:00:00.000000000&#x27;, &#x27;2005-12-16T12:00:00.000000000&#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'>-90.0 -88.75 -87.5 ... 88.75 90.0</div><input id='attrs-68e7d5c7-9948-4395-8c4b-4386a72e8d68' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68e7d5c7-9948-4395-8c4b-4386a72e8d68' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9f528fa-2fe6-4a96-b3d5-a184cb228fd5' class='xr-var-data-in' type='checkbox'><label for='data-b9f528fa-2fe6-4a96-b3d5-a184cb228fd5' 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([-90.  , -88.75, -87.5 , -86.25, -85.  , -83.75, -82.5 , -81.25, -80.  ,\n",
+       "       -78.75, -77.5 , -76.25, -75.  , -73.75, -72.5 , -71.25, -70.  , -68.75,\n",
+       "       -67.5 , -66.25, -65.  , -63.75, -62.5 , -61.25, -60.  , -58.75, -57.5 ,\n",
+       "       -56.25, -55.  , -53.75, -52.5 , -51.25, -50.  , -48.75, -47.5 , -46.25,\n",
+       "       -45.  , -43.75, -42.5 , -41.25, -40.  , -38.75, -37.5 , -36.25, -35.  ,\n",
+       "       -33.75, -32.5 , -31.25, -30.  , -28.75, -27.5 , -26.25, -25.  , -23.75,\n",
+       "       -22.5 , -21.25, -20.  , -18.75, -17.5 , -16.25, -15.  , -13.75, -12.5 ,\n",
+       "       -11.25, -10.  ,  -8.75,  -7.5 ,  -6.25,  -5.  ,  -3.75,  -2.5 ,  -1.25,\n",
+       "         0.  ,   1.25,   2.5 ,   3.75,   5.  ,   6.25,   7.5 ,   8.75,  10.  ,\n",
+       "        11.25,  12.5 ,  13.75,  15.  ,  16.25,  17.5 ,  18.75,  20.  ,  21.25,\n",
+       "        22.5 ,  23.75,  25.  ,  26.25,  27.5 ,  28.75,  30.  ,  31.25,  32.5 ,\n",
+       "        33.75,  35.  ,  36.25,  37.5 ,  38.75,  40.  ,  41.25,  42.5 ,  43.75,\n",
+       "        45.  ,  46.25,  47.5 ,  48.75,  50.  ,  51.25,  52.5 ,  53.75,  55.  ,\n",
+       "        56.25,  57.5 ,  58.75,  60.  ,  61.25,  62.5 ,  63.75,  65.  ,  66.25,\n",
+       "        67.5 ,  68.75,  70.  ,  71.25,  72.5 ,  73.75,  75.  ,  76.25,  77.5 ,\n",
+       "        78.75,  80.  ,  81.25,  82.5 ,  83.75,  85.  ,  86.25,  87.5 ,  88.75,\n",
+       "        90.  ])</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'>0.0 1.875 3.75 ... 356.2 358.1</div><input id='attrs-ac3ac245-2649-4011-ba22-4c6ab00e8406' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac3ac245-2649-4011-ba22-4c6ab00e8406' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2312919-82fd-4a37-8e2d-fb6b76ba59c3' class='xr-var-data-in' type='checkbox'><label for='data-a2312919-82fd-4a37-8e2d-fb6b76ba59c3' 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.   ,   1.875,   3.75 ,   5.625,   7.5  ,   9.375,  11.25 ,  13.125,\n",
+       "        15.   ,  16.875,  18.75 ,  20.625,  22.5  ,  24.375,  26.25 ,  28.125,\n",
+       "        30.   ,  31.875,  33.75 ,  35.625,  37.5  ,  39.375,  41.25 ,  43.125,\n",
+       "        45.   ,  46.875,  48.75 ,  50.625,  52.5  ,  54.375,  56.25 ,  58.125,\n",
+       "        60.   ,  61.875,  63.75 ,  65.625,  67.5  ,  69.375,  71.25 ,  73.125,\n",
+       "        75.   ,  76.875,  78.75 ,  80.625,  82.5  ,  84.375,  86.25 ,  88.125,\n",
+       "        90.   ,  91.875,  93.75 ,  95.625,  97.5  ,  99.375, 101.25 , 103.125,\n",
+       "       105.   , 106.875, 108.75 , 110.625, 112.5  , 114.375, 116.25 , 118.125,\n",
+       "       120.   , 121.875, 123.75 , 125.625, 127.5  , 129.375, 131.25 , 133.125,\n",
+       "       135.   , 136.875, 138.75 , 140.625, 142.5  , 144.375, 146.25 , 148.125,\n",
+       "       150.   , 151.875, 153.75 , 155.625, 157.5  , 159.375, 161.25 , 163.125,\n",
+       "       165.   , 166.875, 168.75 , 170.625, 172.5  , 174.375, 176.25 , 178.125,\n",
+       "       180.   , 181.875, 183.75 , 185.625, 187.5  , 189.375, 191.25 , 193.125,\n",
+       "       195.   , 196.875, 198.75 , 200.625, 202.5  , 204.375, 206.25 , 208.125,\n",
+       "       210.   , 211.875, 213.75 , 215.625, 217.5  , 219.375, 221.25 , 223.125,\n",
+       "       225.   , 226.875, 228.75 , 230.625, 232.5  , 234.375, 236.25 , 238.125,\n",
+       "       240.   , 241.875, 243.75 , 245.625, 247.5  , 249.375, 251.25 , 253.125,\n",
+       "       255.   , 256.875, 258.75 , 260.625, 262.5  , 264.375, 266.25 , 268.125,\n",
+       "       270.   , 271.875, 273.75 , 275.625, 277.5  , 279.375, 281.25 , 283.125,\n",
+       "       285.   , 286.875, 288.75 , 290.625, 292.5  , 294.375, 296.25 , 298.125,\n",
+       "       300.   , 301.875, 303.75 , 305.625, 307.5  , 309.375, 311.25 , 313.125,\n",
+       "       315.   , 316.875, 318.75 , 320.625, 322.5  , 324.375, 326.25 , 328.125,\n",
+       "       330.   , 331.875, 333.75 , 335.625, 337.5  , 339.375, 341.25 , 343.125,\n",
+       "       345.   , 346.875, 348.75 , 350.625, 352.5  , 354.375, 356.25 , 358.125])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-69b7416d-eba0-4ac6-ad36-ab6d6d8c2cdf' class='xr-section-summary-in' type='checkbox'  checked><label for='section-69b7416d-eba0-4ac6-ad36-ab6d6d8c2cdf' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>surface_temperature</dd><dt><span>long_name :</span></dt><dd>Surface Temperature</dd><dt><span>comment :</span></dt><dd>&quot;&quot;skin&quot;&quot; temperature (i.e., SST for open ocean)</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>history :</span></dt><dd>2012-01-17T03:16:09Z altered by CMOR: replaced missing value flag (-1.07374e+09) with standard missing value (1e+20).</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_ACCESS1-0_historical_r0i0p0.nc areacella: areacella_fx_ACCESS1-0_historical_r0i0p0.nc</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'ts' (time: 1872, lat: 145, lon: 192)>\n",
+       "[52116480 values with dtype=float32]\n",
+       "Coordinates:\n",
+       "  * time     (time) datetime64[ns] 1850-01-16T12:00:00 ... 2005-12-16T12:00:00\n",
+       "  * lat      (lat) float64 -90.0 -88.75 -87.5 -86.25 ... 86.25 87.5 88.75 90.0\n",
+       "  * lon      (lon) float64 0.0 1.875 3.75 5.625 7.5 ... 352.5 354.4 356.2 358.1\n",
+       "Attributes:\n",
+       "    standard_name:     surface_temperature\n",
+       "    long_name:         Surface Temperature\n",
+       "    comment:           \"\"skin\"\" temperature (i.e., SST for open ocean)\n",
+       "    units:             K\n",
+       "    cell_methods:      time: mean\n",
+       "    cell_measures:     area: areacella\n",
+       "    history:           2012-01-17T03:16:09Z altered by CMOR: replaced missing...\n",
+       "    associated_files:  baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation..."
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ts"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "51bf1c04-a1fd-4e5b-a560-1d74405ce66f",
+   "metadata": {},
+   "source": [
+    "## 1. Temporal Average\n",
+    "\n",
+    "### 1.1 Default (`center_times=False`, `weighted=True`)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "553043f8-3982-4300-b026-6e4a73ad05b9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_ave_month = ds.temporal.average(\"ts\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "347e0e12-418c-4644-94dc-b405eedcaeb7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_ave_month = ds.temporal.average(\"ts\", weighted=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "40e19a21-cf46-46cf-ab5e-a48682008d40",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(145, 192)"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_ave_month.ts.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "c20553c6-3095-4e91-944e-125ad3076731",
+   "metadata": {},
+   "outputs": [
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+       "}\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:   (lat: 145, bnds: 2, lon: 192)\n",
+       "Coordinates:\n",
+       "  * lat       (lat) float64 -90.0 -88.75 -87.5 -86.25 ... 86.25 87.5 88.75 90.0\n",
+       "  * lon       (lon) float64 0.0 1.875 3.75 5.625 7.5 ... 352.5 354.4 356.2 358.1\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    lat_bnds  (lat, bnds) float64 -90.0 -89.38 -89.38 ... 89.38 89.38 90.0\n",
+       "    lon_bnds  (lon, bnds) float64 -0.9375 0.9375 0.9375 ... 357.2 357.2 359.1\n",
+       "    ts        (lat, lon) float64 224.6 224.6 224.6 224.6 ... 253.8 253.8 253.8\n",
+       "Attributes: (12/28)\n",
+       "    institution:            CSIRO (Commonwealth Scientific and Industrial Res...\n",
+       "    institute_id:           CSIRO-BOM\n",
+       "    experiment_id:          historical\n",
+       "    source:                 ACCESS1-0 2011. Atmosphere: AGCM v1.0 (N96 grid-p...\n",
+       "    model_id:               ACCESS1-0\n",
+       "    forcing:                GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4...\n",
+       "    ...                     ...\n",
+       "    table_id:               Table Amon (27 April 2011) 9c851218e3842df9a62ef3...\n",
+       "    title:                  ACCESS1-0 model output prepared for CMIP5 historical\n",
+       "    parent_experiment:      pre-industrial control\n",
+       "    modeling_realm:         atmos\n",
+       "    realization:            1\n",
+       "    cmor_version:           2.8.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f70ef189-037f-4b82-b062-4239f02488c4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f70ef189-037f-4b82-b062-4239f02488c4' 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'>lat</span>: 145</li><li><span>bnds</span>: 2</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-f791d3e6-6654-42f3-9ef0-557957a16b53' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f791d3e6-6654-42f3-9ef0-557957a16b53' class='xr-section-summary' >Coordinates: <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 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'>-90.0 -88.75 -87.5 ... 88.75 90.0</div><input id='attrs-a5f31dab-9993-4bed-aeb2-acd91868d7d3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a5f31dab-9993-4bed-aeb2-acd91868d7d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1cf5f65c-72c9-4600-a7c6-f4dc641e8013' class='xr-var-data-in' type='checkbox'><label for='data-1cf5f65c-72c9-4600-a7c6-f4dc641e8013' 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([-90.  , -88.75, -87.5 , -86.25, -85.  , -83.75, -82.5 , -81.25, -80.  ,\n",
+       "       -78.75, -77.5 , -76.25, -75.  , -73.75, -72.5 , -71.25, -70.  , -68.75,\n",
+       "       -67.5 , -66.25, -65.  , -63.75, -62.5 , -61.25, -60.  , -58.75, -57.5 ,\n",
+       "       -56.25, -55.  , -53.75, -52.5 , -51.25, -50.  , -48.75, -47.5 , -46.25,\n",
+       "       -45.  , -43.75, -42.5 , -41.25, -40.  , -38.75, -37.5 , -36.25, -35.  ,\n",
+       "       -33.75, -32.5 , -31.25, -30.  , -28.75, -27.5 , -26.25, -25.  , -23.75,\n",
+       "       -22.5 , -21.25, -20.  , -18.75, -17.5 , -16.25, -15.  , -13.75, -12.5 ,\n",
+       "       -11.25, -10.  ,  -8.75,  -7.5 ,  -6.25,  -5.  ,  -3.75,  -2.5 ,  -1.25,\n",
+       "         0.  ,   1.25,   2.5 ,   3.75,   5.  ,   6.25,   7.5 ,   8.75,  10.  ,\n",
+       "        11.25,  12.5 ,  13.75,  15.  ,  16.25,  17.5 ,  18.75,  20.  ,  21.25,\n",
+       "        22.5 ,  23.75,  25.  ,  26.25,  27.5 ,  28.75,  30.  ,  31.25,  32.5 ,\n",
+       "        33.75,  35.  ,  36.25,  37.5 ,  38.75,  40.  ,  41.25,  42.5 ,  43.75,\n",
+       "        45.  ,  46.25,  47.5 ,  48.75,  50.  ,  51.25,  52.5 ,  53.75,  55.  ,\n",
+       "        56.25,  57.5 ,  58.75,  60.  ,  61.25,  62.5 ,  63.75,  65.  ,  66.25,\n",
+       "        67.5 ,  68.75,  70.  ,  71.25,  72.5 ,  73.75,  75.  ,  76.25,  77.5 ,\n",
+       "        78.75,  80.  ,  81.25,  82.5 ,  83.75,  85.  ,  86.25,  87.5 ,  88.75,\n",
+       "        90.  ])</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'>0.0 1.875 3.75 ... 356.2 358.1</div><input id='attrs-800e7512-44dc-4c1f-b2c0-b2f13c60aacf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-800e7512-44dc-4c1f-b2c0-b2f13c60aacf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4687264c-132b-41cb-8c79-0a704ea0c589' class='xr-var-data-in' type='checkbox'><label for='data-4687264c-132b-41cb-8c79-0a704ea0c589' 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.   ,   1.875,   3.75 ,   5.625,   7.5  ,   9.375,  11.25 ,  13.125,\n",
+       "        15.   ,  16.875,  18.75 ,  20.625,  22.5  ,  24.375,  26.25 ,  28.125,\n",
+       "        30.   ,  31.875,  33.75 ,  35.625,  37.5  ,  39.375,  41.25 ,  43.125,\n",
+       "        45.   ,  46.875,  48.75 ,  50.625,  52.5  ,  54.375,  56.25 ,  58.125,\n",
+       "        60.   ,  61.875,  63.75 ,  65.625,  67.5  ,  69.375,  71.25 ,  73.125,\n",
+       "        75.   ,  76.875,  78.75 ,  80.625,  82.5  ,  84.375,  86.25 ,  88.125,\n",
+       "        90.   ,  91.875,  93.75 ,  95.625,  97.5  ,  99.375, 101.25 , 103.125,\n",
+       "       105.   , 106.875, 108.75 , 110.625, 112.5  , 114.375, 116.25 , 118.125,\n",
+       "       120.   , 121.875, 123.75 , 125.625, 127.5  , 129.375, 131.25 , 133.125,\n",
+       "       135.   , 136.875, 138.75 , 140.625, 142.5  , 144.375, 146.25 , 148.125,\n",
+       "       150.   , 151.875, 153.75 , 155.625, 157.5  , 159.375, 161.25 , 163.125,\n",
+       "       165.   , 166.875, 168.75 , 170.625, 172.5  , 174.375, 176.25 , 178.125,\n",
+       "       180.   , 181.875, 183.75 , 185.625, 187.5  , 189.375, 191.25 , 193.125,\n",
+       "       195.   , 196.875, 198.75 , 200.625, 202.5  , 204.375, 206.25 , 208.125,\n",
+       "       210.   , 211.875, 213.75 , 215.625, 217.5  , 219.375, 221.25 , 223.125,\n",
+       "       225.   , 226.875, 228.75 , 230.625, 232.5  , 234.375, 236.25 , 238.125,\n",
+       "       240.   , 241.875, 243.75 , 245.625, 247.5  , 249.375, 251.25 , 253.125,\n",
+       "       255.   , 256.875, 258.75 , 260.625, 262.5  , 264.375, 266.25 , 268.125,\n",
+       "       270.   , 271.875, 273.75 , 275.625, 277.5  , 279.375, 281.25 , 283.125,\n",
+       "       285.   , 286.875, 288.75 , 290.625, 292.5  , 294.375, 296.25 , 298.125,\n",
+       "       300.   , 301.875, 303.75 , 305.625, 307.5  , 309.375, 311.25 , 313.125,\n",
+       "       315.   , 316.875, 318.75 , 320.625, 322.5  , 324.375, 326.25 , 328.125,\n",
+       "       330.   , 331.875, 333.75 , 335.625, 337.5  , 339.375, 341.25 , 343.125,\n",
+       "       345.   , 346.875, 348.75 , 350.625, 352.5  , 354.375, 356.25 , 358.125])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-91b10566-e99f-4ee3-bd21-b784be06aa0e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-91b10566-e99f-4ee3-bd21-b784be06aa0e' class='xr-section-summary' >Data variables: <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>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'>...</div><input id='attrs-71bbc002-7e59-4d72-8390-d429fa3462ff' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-71bbc002-7e59-4d72-8390-d429fa3462ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a88284c-c83a-4551-87ac-7603cdf87330' class='xr-var-data-in' type='checkbox'><label for='data-0a88284c-c83a-4551-87ac-7603cdf87330' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-90.   , -89.375],\n",
+       "       [-89.375, -88.125],\n",
+       "       [-88.125, -86.875],\n",
+       "       ...,\n",
+       "       [ 86.875,  88.125],\n",
+       "       [ 88.125,  89.375],\n",
+       "       [ 89.375,  90.   ]])</pre></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'>...</div><input id='attrs-21ae224f-c048-483f-a46f-46a22cdc3e23' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-21ae224f-c048-483f-a46f-46a22cdc3e23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-071cf9d0-eef3-4a39-bdcd-8621faddc0d6' class='xr-var-data-in' type='checkbox'><label for='data-071cf9d0-eef3-4a39-bdcd-8621faddc0d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ -0.9375,   0.9375],\n",
+       "       [  0.9375,   2.8125],\n",
+       "       [  2.8125,   4.6875],\n",
+       "       ...,\n",
+       "       [353.4375, 355.3125],\n",
+       "       [355.3125, 357.1875],\n",
+       "       [357.1875, 359.0625]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ts</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>224.6 224.6 224.6 ... 253.8 253.8</div><input id='attrs-cf36bc8c-a5c7-46f7-96ba-24012027d154' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cf36bc8c-a5c7-46f7-96ba-24012027d154' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3202885c-9e42-448e-9c64-0dc5c4597773' class='xr-var-data-in' type='checkbox'><label for='data-3202885c-9e42-448e-9c64-0dc5c4597773' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>surface_temperature</dd><dt><span>long_name :</span></dt><dd>Surface Temperature</dd><dt><span>comment :</span></dt><dd>&quot;&quot;skin&quot;&quot; temperature (i.e., SST for open ocean)</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>history :</span></dt><dd>2012-01-17T03:16:09Z altered by CMOR: replaced missing value flag (-1.07374e+09) with standard missing value (1e+20).</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_ACCESS1-0_historical_r0i0p0.nc areacella: areacella_fx_ACCESS1-0_historical_r0i0p0.nc</dd><dt><span>operation :</span></dt><dd>temporal_avg</dd><dt><span>mode :</span></dt><dd>average</dd><dt><span>freq :</span></dt><dd>month</dd><dt><span>weighted :</span></dt><dd>True</dd><dt><span>center_times :</span></dt><dd>False</dd></dl></div><div class='xr-var-data'><pre>array([[224.63190177, 224.63190177, 224.63190177, ..., 224.63190177,\n",
+       "        224.63190177, 224.63190177],\n",
+       "       [228.32156131, 228.26436586, 228.20520529, ..., 228.48919971,\n",
+       "        228.43403387, 228.37894071],\n",
+       "       [229.51051546, 229.37391584, 229.23693873, ..., 229.89809979,\n",
+       "        229.77730198, 229.646766  ],\n",
+       "       ...,\n",
+       "       [254.43141738, 254.46242388, 254.49356349, ..., 254.32908235,\n",
+       "        254.36883088, 254.39857257],\n",
+       "       [254.19129091, 254.20466136, 254.21739569, ..., 254.14740382,\n",
+       "        254.15849709, 254.17515679],\n",
+       "       [253.78937694, 253.78937694, 253.78937694, ..., 253.78937694,\n",
+       "        253.78937694, 253.78937694]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dcfe2675-2d34-48cb-8f5f-9ac38dd400f3' class='xr-section-summary-in' type='checkbox'  ><label for='section-dcfe2675-2d34-48cb-8f5f-9ac38dd400f3' class='xr-section-summary' >Attributes: <span>(28)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>institution :</span></dt><dd>CSIRO (Commonwealth Scientific and Industrial Research Organisation, Australia), and BOM (Bureau of Meteorology, Australia)</dd><dt><span>institute_id :</span></dt><dd>CSIRO-BOM</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>source :</span></dt><dd>ACCESS1-0 2011. Atmosphere: AGCM v1.0 (N96 grid-point, 1.875 degrees EW x approx 1.25 degree NS, 38 levels); ocean: NOAA/GFDL MOM4p1 (nominal 1.0 degree EW x 1.0 degrees NS, tripolar north of 65N, equatorial refinement to 1/3 degree from 10S to 10 N, cosine dependent NS south of 25S, 50 levels); sea ice: CICE4.1 (nominal 1.0 degree EW x 1.0 degrees NS, tripolar north of 65N, equatorial refinement to 1/3 degree from 10S to 10 N, cosine dependent NS south of 25S); land: MOSES2 (1.875 degree EW x 1.25 degree NS, 4 levels</dd><dt><span>model_id :</span></dt><dd>ACCESS1-0</dd><dt><span>forcing :</span></dt><dd>GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4, CFC11, CFC12, CFC113, HCFC22, HFC125, HFC134a)</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p1</dd><dt><span>branch_time :</span></dt><dd>109207.0</dd><dt><span>contact :</span></dt><dd>The ACCESS wiki: http://wiki.csiro.au/confluence/display/ACCESS/Home. Contact Tony.Hirst@csiro.au regarding the ACCESS coupled climate model. Contact Peter.Uhe@csiro.au regarding ACCESS coupled climate model CMIP5 datasets.</dd><dt><span>history :</span></dt><dd>CMIP5 compliant file produced from raw ACCESS model output using the ACCESS Post-Processor and CMOR2. 2012-01-17T03:16:09Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>references :</span></dt><dd>See http://wiki.csiro.au/confluence/display/ACCESS/ACCESS+Publications</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>3ba59dfe-51df-471d-ae2f-74959d08bd9f</dd><dt><span>version_number :</span></dt><dd>v20120115</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>creation_date :</span></dt><dd>2012-01-17T03:16:09Z</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (27 April 2011) 9c851218e3842df9a62ef38b1e2575bb</dd><dt><span>title :</span></dt><dd>ACCESS1-0 model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>1</dd><dt><span>cmor_version :</span></dt><dd>2.8.0</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:   (lat: 145, bnds: 2, lon: 192)\n",
+       "Coordinates:\n",
+       "  * lat       (lat) float64 -90.0 -88.75 -87.5 -86.25 ... 86.25 87.5 88.75 90.0\n",
+       "  * lon       (lon) float64 0.0 1.875 3.75 5.625 7.5 ... 352.5 354.4 356.2 358.1\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    lat_bnds  (lat, bnds) float64 ...\n",
+       "    lon_bnds  (lon, bnds) float64 ...\n",
+       "    ts        (lat, lon) float64 224.6 224.6 224.6 224.6 ... 253.8 253.8 253.8\n",
+       "Attributes: (12/28)\n",
+       "    institution:            CSIRO (Commonwealth Scientific and Industrial Res...\n",
+       "    institute_id:           CSIRO-BOM\n",
+       "    experiment_id:          historical\n",
+       "    source:                 ACCESS1-0 2011. Atmosphere: AGCM v1.0 (N96 grid-p...\n",
+       "    model_id:               ACCESS1-0\n",
+       "    forcing:                GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4...\n",
+       "    ...                     ...\n",
+       "    table_id:               Table Amon (27 April 2011) 9c851218e3842df9a62ef3...\n",
+       "    title:                  ACCESS1-0 model output prepared for CMIP5 historical\n",
+       "    parent_experiment:      pre-industrial control\n",
+       "    modeling_realm:         atmos\n",
+       "    realization:            1\n",
+       "    cmor_version:           2.8.0"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_ave_month"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "66e7ac8a-a4d2-428c-952f-427dde5cb6ab",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x1645a52b0>"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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qTylpTT7SSdcEXSkf7dRGdrtMTyKGVkGIkGYxwSQhRJKykf4CoEGFGNnC0ff4yYRjI7klJ5uEiiFBV5hw2CDYIn+EsbmjibVLEEn4yU3eZ0fWNzFALmLLUlHS7yPbTJPwfP2txOfTFj3mBS4DtCCoqimJHLsSRfi4flpGMhUovs2uuck+a59clmQKNx6JfK45/ISa0mJpzano55BjipPvFPpdXDBJdlIJiARGeh8uq3kKQBNKm7ldnId4zrb4n6N2KfbN6QmhslFLkmIySXeIZi33++oJgwoNJSotyGoLmWIvHNZJN9VHKvbn0uDQhcSIESNGXJlYj+P6qOPYCAkiRpHVnlLy+Q6JFaGZsLMwasq9FzZRXjSPwCfHWXWnnOeemiov5igv5p4eUrmO191l4WkVGhlrBOrJNZ1xyJuoxX7XX1dGPAuabev9Sg1R1ocS1BdpivIUxO0JSshxFRRZAFHVTMVCY2fBFaFBsURti1Pktd0xlFggDWupRetvc/D7U+R2B/t8lbaUhDD45POVmrw7R4tkxigKLbmupMyYKMpHaFgHCbUTdVVaBC10YBcaFoI7Xic/vbTwJIXo8jPsbKDq0M/FKUTWIVWI7tfQhNYiEHylnjKgGWrPPssC0W8dJQgS+f7UUxNZ5WkkaUkQoDd0GJcFAxvBUV1MKsymJtxJJtMC8AEtQExBHwTmEY9C4opCRpaH7BAS2tJL88rctqOWAJj6TARQ2wBiS7PYt0NXqjnx+usQ4BLrFEf0ANvJ1ScREYWJykZTOfMZaJls3RUk3cEwdav8iyrn82TmFbLM1OQRuzMOwsW1Ty3nuU2iqFs0Xyb0SCRAknYaIbCpAPMHygZbtqX315jRYbhyEVrKE47Oi2KACXF9JBKXS6m0SFmwz8Vl1Kf0XYe/IG06jfySUXDxgWgXri3bG20koCocr4vkNxDnUhZWn9NT2IgmcU+pIMjkjy/aVHFoq6OX6k2TJFjP7MGZKf3vPmOikW8YQVAUNYrcCIlpXmGS15hkRstSxNAcNH3NFOaE3iexGuqVippdmThWQmLEiBEjLhcYhLKz2uLxwbG5QwIjV8KSaNEWNAj3XdzAhR1jy5rqrvZ8BWR5Lagi8g5J1sI7CdhciIRe4vAVQnuS14ClgthehIhFJBQ3o4tSJYWj/8KXBs8iNGjhFIxOIzQTs0TUSmRJSNqLKbKOjAWWUGruo19cxm6QpT7ctbJm51KHa0MlTu/R9a+h1LEo6WA1/Da6hxHyTRCO71QSk+0yz0JGKUmLQD6zRhvcvF9Zt4vTDktKKepI8llYcdx2vLtaZa0CURojrbYqx7ArPU+VsSKctcAZA67f0xp1XSDbC/0mkWPDCqhsTke1FSKYdMHgHKhtvgNNamSutEau42hFMS73qhw1KxQ2kWeSV1BgnxA7pNDeqmCMjusrCkShJpNCe0RTVStc3Jv4wcUiRC7Pa+RZqNe0qEI4LCdhKVoH6sm9vJ6qgRQgHIfZWsrKv2+SEnB8hBJvtQvHFSXK/bEQ21hw7SLW0dAfJEIUEU9OkppJ/AXychHI1MJiz02YF9ut0bEsuslPFO423fNTiKKLGvcrqSNCeE4pFZb4K/wEljMw054KAhAmQsVgxT7pkTm+HqRPpmeecYLATfBUU1Pwu2bE7wtGfJz8fe39yDpHDcqrRYAwYspKhqqmWePOX+IFWgvdJAW9Q3nSZDk7Qc8F+yJ62URDn1qA7zESRVXB3waYJDlXjLA6wdBWKLBi0ERjtmVib09s7OGqDVNyR7OJKqxs5+48u43KOoAWFwucOr2LjcJQUS660SmLGuE91H0/4gpg0Eg3jRgxYsSIboyO6ysIhJAbkTqrL5QmbOSTZ06ZY31SDWM6sZqHtSJcVVhFQuPPhHUAG2ctNGFjEQgeQ6zG1bAsEKJfjDYnNXmhscp97hpdfJMoIYIaTcuhydCEs/sUoQ5+gplCUqKlcGpxLIky6o3oqi6nNCfnsbBoZJ6GpMHcPckEyZQKmjhLQpvn7vImagol2zM2QQZ2n1mbPPzGEd3WsFxiq0466jlLLJKE/oEIFGhYXWI4yURHEpFsbkhEq78JayENAPCJeYRowSldEFQtVylMxiEEHSdqKdVTBufhuWGqoXJHDdXIJ4z5wlZZvreAykKbehqc0/WJGmQppdnWAic35rhuy2ThTbJgulTalL+Z16YD1568EKKXTjHuN+1Yeg/BkQ2sz3HNjDEE9koCwdBNbiC4gXTHuZOYLwzhydr4CByveWK2h4kd1JoJizrzgy7PtKjj5ISB/Y5At7iV5/x7yhzeLxsa66gpTy8x+/3UMxHLsdzIlo04bTFJZhTVc+J0ApIvfzrZpeE4rR1L6C0rEyVF5EIhSQOo4ZOm3On+PPl+yesrNqu+Ov+F9Fs4odcW0eOO3Ta8BhEDNsmRXPSSm5hzBmxhOuNXYZCjTdqegWO+HGuRUn72TNbhu5mo2d9TJAglLSjvy0HSaRzaZM0hGdOPOXuoFCCpYkCIQ35l4cXKdkeUmJdUlZnM3W9KUWgwMgZPrHJW1P4Zuvds835m4t47myOqF5XB1FoCkJ8oceqkoZROzS5iMy8DdSz8iyozE70THCcne+FxtYzX1A/RVcxz/6C1UVdHGcdGSIwYMWLE5QQDWIzRTVcu7rtoFvTdK3OvXanMREdMWhYfUcKCAGxcdUQpEWqXZKWVtwCcVeG+Rwqm5QNkbRuSDsQ2s1fsY6GhwlozrcdLA0AsAgMmo3l2WQhpc51e1viYSGO1pSgkxRWoL3NcoDniBWtsF0XX2LepC1OLx9/TRXGCoJh4wqHO0IkSxSSOUNN1sOJYlHSPrSuTgOkIRm8pSFrQ99NQMdICdNqzrhRongF2bXQWiZTkLQrXt+RZy+eQUmYcX88tcAWXrCkS9tL8Cn+OpOmSS/tIKqnpy2FSUei3pN4UA4oj68EFgpBtzlnt9Y07uLhtogrV3OYZbRuqd3NzD/ezzmlnJbTlNLiAlK4yO0CyCFDyHPvO2w8Y64+YOoo4NkKCEQ8QNzjzTEPZl0ApjUlWe0GgKFBPmgmzvPI1mRZ1WA5MMyyF4qgLDS2L+HVMvG6il7RAI3LGHZsMYJm856kGyT2L45ITo4mQKDlBRumkVJRvg2KaKp1UkluOwyVDUp65PoV6PhMOE3huP7v6SDbZDbD8d6GD74bsKmMAKNeYnVhEZZ+d8E5r8mgO0UW1VqgrZcKZgdBH8UzI1UHP7QQvhI0/lEy/T2ybxReKvMbVmzv+epoJd18wYTsX5wWqveQVc/NxlnJmcme8NT2KsiAkuCZBYYn7EoLcty5/+1aI68shw/G57jH5xyKoLScMlaijBgCzaYniWnPi3l6Ouswws0lxpzYveipIMyFXutW/qEi3VlCIEQZjLoqMacFtVmv0I4whsCNGjBgxohVGMR2FxBUDQhzBcHoWIh3c50orX/UVaNZwKXXmLQlZTpjIOa2tNiuyjZi5nQaC1fIpaM8+akdqaZ0mcGg3WBDiOs45mqiLxolsKRZJryTX832OilCJ/xnNBDNzwbgvS3yB6ap6zsnp23GRMRPtNfawvLGgdKw1uLG9h41pGdXk6YNzLFa1QpVlqK0jW2uKfjdKrUHxVR5bFDWu3t7BLDda8CyrAlVpteer7Hhb1Bk+duZ+AIDdixOwVqGkvI4vQkp+DteOItX8NufgB6BI/BYU1e3imkAuf0X+lOmYS35TE5UVtiXMnK8QC1fWpeU55plGnunouebsrPsazIRpbjzl0yxUWE4tBWk9pPlPstSGttSPoiaFbI/GwvKe6yvLsdrSpFcqjo2QAMKg0EzeXL1mY8fvzzONSqvGS+3OKXWIbspUMGUVM2qQmE85WtFO0stSUGndDMIxlHqYqNtoJgd3nGePokO5ZZt9Z7WrMMdNv4eYdKKJisnzBz48VFIXMulOzm+uiGAHZHFAGVrJzq8g5jDy3HhCq9Uh413Zks/umaSTSpfQLZSGzmtU9tmUVeZpqi4h737HItM4tTn32wpVR9E36fFu2yyr8LCr7wYAfGpnG/ec3/JCylBfVtArjvl8sbKii3KTfZSVAJjZ+yhYUYgkYzZCw1JT6mJYVldnifIiKUAHL6iEwEALOymUHq5JCHoztgtPC+ronsy+9sXUNFOghLTwF6raCgr37IHKSiy32l3oPkfv4oVqit3KRDnKqKiDYF2WBBHdCOA3AFwP89bdwswvIqIvAPAfAZyAWVfn25n5nD3nuQCeAZPe+Gxmft2BO9KBYyUkRowYMeJyYY2LDlUAfpCZ30FE2wDeTkSvB/CfAPwQM7+RiL4LwA8D+FdE9EgA3wbgUTBrXL+BiB5+qZYwPZZCos+5tZmXkfXg6Ih0JTtmAqzWWVvNx+sMBGE9cFzaiAmZM4+tuhvyLTjKt4joFBkz7/73SmHzeO9jJGvN6KY2bOpGkaBvpI+RzYI5wunpnMjOivCVZdsUbelUJkSJcI36SO4BZSK6yeUliHwAt2BMbqPPFrsTfz7ZYIPZpARRsxR01LWW5+pQ2A5MsjpEq6EZvVZrwtTm0JzcmHvLNFM6cqxGY4iN9toW43/91nksqgy7C3NPpcqgBZ2nrDXhzvPRcuQCHoKG7scIGy1fZ2Kf+B1YEzi39zQVJUnmClTF9aEi2jBDUq8recCeqjTau09K1ApVaSZNsmtKS0vCPQt5nyk0Eyoo/2wUWEQ8GdM8k+dZaySyKGzbijQ0h+TY9edJrCeZzi7VfIf9fJ6IPgDgBgCPAPBn9rDXA3gdgH8F4MkAXsHMewA+SkQfBvAlAN584M604NgJibaBJ8uGu6zNFJrJ+iEsZw3ps1A2ATe0HQJM4rZYJPA4X4Ivq6QV6o5xapZHDedIKkpOEP46CY8lh6pOr+HoADGBk4KNRAp8D4eP5rvzF8gkrJQmIhtR48My4+eRn1dgZbbVGxqwGdCUMSgPkWekNFTm+Ow6+HNsX5QNKy16XvQ26qkxHuz3QtXRb1drFUW2bWW19ztQOvETD0qi0gi0Jxi4/sR5PzbuuHASF/dskqf9raVg8GNWKi1Ix5f5rpRQRvxvbRUHn4QHTz1xpsG1CpFljGgAcVp0sfG+CFqQhD/FU5iGTitV5id4zRQX51sSjqrFYHQUYUWZOc82M1XBHwQVUz9GQIQ6TzlpnMhNPaiFXov2b+im4T6Ja4joVvH9Fma+JT2IiG6CWe/6rQDeC+BJAH4PwD8GcKM97AYAbxGn3W63XRIcOyExYsSIEZcHK61MdzczP663NaITAF4F4DnMfM5STC8mon8N4LUAFv7CTazLG9/AsREShCTxRkQ9VEJDlCani4gAZKSEqx5J0BRonliDC79RZq9Ze42cQUlEUTjeWCpaaPYutt9dQ+Zm+HvzFkVzHDiNmwW15ZQrXZukJW3rUaEmX7HT1djxbRN5i8ElkbokKWlJuLwLEjQRcXCWc0VR2YhqkyH9k6EGkLlXlcVrEgPGgmOmsF5xrnH1yRCAkFJIffSSPyZ5h4jY/3bMBCjtHakbhXkX25zTQExf9mnE6Xic2JUTAeDEdC9ynMsx1Wbp+srFHGhPd46zgBQba9XuhcqCZh9Fc2UE1ho8sdevCbzIQPZ5k6w5ZWtvtVUSJmVNWGf1ZHGkBnOYRGutonXno3sbmORWsQLqHCorxbl2jICQUUzJXygn3mrYzBf+Oq5kz0FhHNeDLYleEFEBIyBexsyvBgBm/iCAr7X7Hw7g79nDb0ewKgDgQQA+uZaOtODYCAln+k1sPWLHUUp6yUU7uO856WAuUlNo6OTFlVpDOjiIXEgs+cnHwQsQpUCko0zumHsOYa8Zhc+SinCobCiv1mSzhcOD8NFNsILCMR4M0J4LAQWo0CL0UgO5cCY4WglxeGa4X7fPHMe1E8oZ2C3BygA26sBAtSQd+miyTPtVxtzLvLFpJuvtWYhGaaOQ5LNphFD6CLHuUGUiRtESOtkrAOQ1Ix48nQCDoMlR+3H5gM3z/phz81msAFifiGsdgH82pMJ9aHaKRui7y4h249Mle8nzXLSUu6RWCnov88qAysO6p6wJrFVKqvo2zR/s90AZuvO1EGSVstSPX/O2ifTZy7DX5qqT4jdrUaRzFVaqy0l7gSGLBh4EZtGhg1NXZLTKXwPwAWZ+odh+HTPfSWZy+QmYSCfAWBUvJ6IXwjiuHwbgbQfuSAcOXUgQ0W0AzsOEclXM/DgiugrAbwO4CSb061uY+b7D6uOIESNGtGFNpcIfD+BpAN5DRO+0234cwMOI6Fn2+6sB/GcAYOb3EdErAbwfJjLqWZcqsgk4AkLC4iuZ+W7x/ccA/DEz/zQR/Zj9/qN9DShibGZG86xYNaKWHKQF0Jae76NWiBrnaBYRLVHcOgUNShzvLJfMOW61KSERLJLYQjARNqEvcfRTfK9V7Vow1kJtKaW6VMGJnCrOmsT6y8qsje36TYJeAkf3E7Fc7rOnHEzOQnA0MihVrtyuLCTMoSZf4sLdk48ws7/B5mQRmujQ7lMroo1Wcvuky1sl56FjX4rWmkIdmm50nj3eWboahC1La11cFJGVSiKAAjDOa3cfJirLWa0hMgtwv4HtC8cO8FrQTSZCSvQ/Y+hTMnkUPlqOFJDOP5T89o4mLPK6tb5ZG2QinHt28rN/XlmNiaUBc1Vjoipv9aXJcppVZF1s53E+hH8vBV11EJhS4Qenm5j5TWj3MwDAizrOuRnAzQe++AAcFSGR4skAvsJ+/nUAf4oBQmKaVbhYm4gR/xITIgqp6qGM3PHufD8IqXl8uixiK4+c0Fu1MhnfGXOjPUVGgJAIZ5RRLHWtfKSLmRgQjtOEes/OzHsq8MnTOg6BbSn+1liGVRzgX3KRKeyiWWTilzncvrgZvH/E0WnuGpONEtXCDLkaKsoslkgL3LnnEx/TMkkLaqntvL7icPuhlhrXd0Kig36KrsHA6YnJzJ5XORZ17id/ACiVoC9Je99VkdWhaJ5Wnb6MmimmajR5f4UcV747Ki6FT0qMCwkheGbTMgptrVlBeSHRfJ5emFGTkk2fkft/omrM7KReqBo51RE1KPsFpLWd4uM21iQcJD4TCvwdhcIjDOCPiOjtRPRMu+3+NnbYxRBf13YiET2TiG4lolsv3je/TN0dMWLECOOT0KwG/V3JOAqWxOOZ+ZNEdB2A1xPRB4eeaOOMbwGAqz/vWr5YFz4932kUizrzDqtFnfkqk4AtywHncE0sAgrUU5qEkzq0UwvFIVpf115fnp+W5cgUeW3SmO0hmc8dDyTRIeyic8y2qO6OJkMh2Xh4zhnk7sXG1LuSDqRCzoSnaHx569qXkyAyVJTTZonYaKj29tW09teva1t6wpXyJkbmnNNZHOmSamRdEUvLImP6rIi+81qPaaGUln2OHa2xMzz+DuR2wegHbZ3FnfMT/hlUWmHmtO6kHHVGGoVPToStdGvPS8ZgrZW3HjMCahGAoDkkYLrSMl3Rc3GABXsneqFqZIqRW0dwVWfQzgJBjUWdBbqLCUpLCo1bndfu+bl3bqIqbFnaqKA4sMG8e7bWmn3vpYWSpe3bh1GutQrs8bckeoUEEb12QBv3MvN37LcDzPxJ+/+dRPQamMzBTxPRA5j5DiJ6AIA7l7VDYExUZRJotPKCYV7nfnJ2g12asps2wabSmTlWJNqE4yyP7AZXxMGb/7r8GzLZZqJqzOvch+SmvKxmQq1CyGBpqWAiAsTaF8zky53XWiGDRm4Xkq+nCrpy5bA94W8vQCJiyYYrCh+Dn7gVI8u0FxKayX92a3K467vCh5SEC7s26zLD1EYpbc4W2J1PfL8Vseez08k2neyHRDC17R/yeT9t9FFQMqIp7NPIxHc5LrKswlXTXVwozfqhSmRCz+scF6siUJasoOxkOcnqKHovE/SKG1vBJ6GQWaFUawIRIXNrRFhFp205kTQiTKlQcynPdHSN7ek8Us6wmLa26aL1vLImi/jZ9hzFtJXvYWrfv8akb59k6KyKnn0n1pR4zSAfrXYUQUTvHnDYXcz81X0HLLMkPg/A/9XXDwC/NKAj7ScTbQFQNhV9CyYm+KdgQryeDuCn7f+/t99rjBgxYsSlwhFfvjQD8I09+wlmru3FMiHxPGZ+Y98BRPSTyy7Sg/sDeI3VQnMAL2fm/05EfwHglUT0DAB/A5OS3gsioCCNPVaodOatByBe7UrSAbnSIXIi0foVcbSvYoU8qRNj2qihWZnYb/vd0VQXqmlEYZ2czJEr7fu2WxWYuThuZeK4vZWhyMd416yiyrZ7dY5MeH2ZyWvkuiBUlhqq6ljL0TWZvAkAYBPNJB3QXdoXUYiCypTJZ5CWDESCoHHAh3OnswWu2zaL2muEulZ7VYZMVDuttfJRTWkJ9zQ3Qmr9rQ7snm1DKKSl+5I2GrRSyzUyP/ac9iyqBbNJNHNjQRF7y1RXhLLO/G+aZ4EiXSTXSPtcaYUSZgxkYv33TMUTm6Os2pywLoLKXVPSS+5eSbxPcrEgZsKeTVyrtfK/a6FqbOYlNm3Zk1zVjd/XOZlP5AtMyXyukZTUSSIflEimM887dmSHqr5rypPg9UQ3XUJ8NzN/rO8AIvreZY30CglmfuWyBoYc03PuRwB8Qcv2ewD0mkB9UMSY5ZX/7gbudjHHg2b3obST/Ed2r4loopw07DtlCoupuI1cCA33si90HmVHa7GG5Ga+wKLOcaKYi/0hA9xNCu7Yic7C5CBe2opVNPHIsMcir1HVKoQsEmNj6qI4SiiEOkO1VqFUtT3eTfay9r8po62iCConTHK7sl8hagqx0r5EdZSNrjSu277g1w0wAkT5fcyE0mULE0fZ526bQxq51CsIOgRKX7TRavRTew2iNtrJF3u0AsILjai0dUzbVKwwr8yrWdkIJhcimzH78QsA07zq9J2ZMWvHqfXHAc2os9CLZqRU6geTZdKdkiUnbq+QaUaVhXdLZ4QNKxROFAtsZgsvCPKkZHgGE6kIABsqhEGDdSwY0u8AFIKQkvSbIvm814cj7pTe6NpBRD/DzD9qw297MchxbVPCfxjAZ8lzmPmrhpw/YsSIEccNV8Aa179ERP+Smf+b22Czt18Ks3bFIAyNbvodmJTwXwVwyTL7DgoNszLV9bOz3tn1gMlZr/l9Yu9+KKj2WvENG2dxx/wkgEAhBa2s9toMkGikIqGnVBXuW2wFi4SDpjnLjCbvtMmaycR9T00donPlBk6IhJ+JqkMklg4ObrBxYDrTfVHlEZ1GBE9NaZC3opz2N5U0hq9jlaMU0Sdp1BDVHNUBkiuOybIGxgkZPOBEDOt7x6mNOTaK0ltMURy/c1w7TVtpT0e00RidFkBStqGxv8eqkJDWQdv+tI0uyyLrvJ65Bxmho+zz2LPFstwYmle5/2ys4ji+39NUScKojNZzkFVQu9Z2dtbtVFgicnzN8srndLjcH9emFs5bSbW6KEJnEW3mJa6eGtrxRL5ATrXX9GWbDs45Li1hzRkyaF9qRBFDLlYurQf3THzZDI4XGFsXjrhP4msB/HcimjLzq4loBuC/AjgL4B8MbWSokKiY+SX76ORlx0ZW4sbZvT4UzpUMBoDrJudwX7nlM7Ovn5zB1YWpofO/d+6P3WoqOGPtF1JPB5cJ0bP7WGOiKpyzkSnyuImqsZGVfiBtZCUqnflr3G+yG0W7SM5as8LcLre4U05wbj7Dwtbqr7XCxIYhZpn2vDEAbE/2/OQ6yytcLItoEnHI1QKlyjx10cb7y5BJ5y+Y5HXEb6POwBxohqs2d8M1LN3hfDvzOscDt84BMOWazy2mUaZxJmgTRRzRKEMn/u7lK5sUUrSvJxomFSCmr93CoK3NLKWbkokxPW9ix94sq7AQKyaWOvMUkELSBsS4dL+5oyyTNHhZ+NJ2MKI3pR/vquluRL0WQpEqqI7uyaFmwsW6wMXcRLOdzOe4emKExFR1J7VpLxzDeyDXhAAQCQZHNznhkAqXT+8ZJXBP59H7uw4wcKSjm5j5NiJ6IoDX2RSDpwF4KzP/wCrtLAuBvcp+/P+sg+M1ALzqy8z3rtbtESNGjDgm6HD2HxUQ0RfZjz8Cszzq6wH8F7edmd8xpJ1llsTbERds+GGxjwE8dGiHLzUIjA1V4nM2Pw2g3aG0qRaYTUqcrTcBGO1uMzNm9Ml8jkpngZqRjmImXKwnmNuSH7m1EACjMV2oprhYmn2ZiPBwxzpt40S2h1JlvnRIWmLAaDuWDtIZdkqjhZ2bz3Bxr/CRSZsbe17TyxRH0UCZ0lHEVJWFiBDN5CNKFDF2qUDBYVEYZ1U4J7KLq8+zOmho1uIo61BRMyPGll03+PRkHjnfc9Iiz4Rw7ey8/3yimPlnmiahydj5PqRafnssfb8VsQrarIrUYmg71lFrKnKmBs22EM8JQETbSKtqV+RMuHN9Pk9W+TYkxQkAWjiHKx8tp6JtzrKYUHBO3392DifzeXRNR5ltZgtrSTSfiWYVVUgtqG5YEPId9UlpVMf7SEOJz/auw/1DRjQFui0jDYiIRJNAF1spBwXjyNNNvyA+vxsmmtRtYwCDfMrLopseAgBENGPmqO6F5beODKaqwmdt3I2CbLSF+O0KCpOUIsaJzNyKHMTXTc5Ds8IDZ/cBAC5UM3x6YUzVnWoS+wjqHOcWM9/mblX4iTETYXdTVeFkPvdC4US2h5Iz7y/RTP6FA4B7yq0o6/bcnrnGzu4URVFha2ZosmleYdMWh5tlVbQk625VeL9GVZtaUbtW2ChiLOx5J4pFNPlUrEJ0DSnUSnmBKdt3x7trXLBtP2jrrL2GxsLSZNr6YJyAuVBNsWmF68nsIvaKHeyxeTY1i2VfoRvVNWsh6FKkCoGcBC519EkfvRVTUk2h5wRKBkamKr/63k4VqMuFzqHAUSTcbmWfmR2PMjvZja02/t09iwKEWmQrayYoVl5oKNI4VRjl6frJOU8Dun2bNuJoRmW0T6JmhRoqijDy+/zqj9p/d7+STgUCK0Aks8pkwhSZiDp02BT1mqTvZF04ypYEM3/lOtoZ+gb9r4HbRowYMeIzAoy4wGff32FA0E0HOmaZT+J6mLVTN4joCxH085MANgf087KBwJhRoFLSqAfA/KAZtNd+ChFhcSrbxW4+8drdVFXecZ2TRiW0Oc3kNWnNNpqoCteSGmNBta91I7cBxslWWC2p1DmmqsJFMpr5vM5x7oKxJKqdCXgLPv/h9OyidwZPVB3F1c+rHPNE05yXZt9emeOcMlpqeWIX25M94QxEFP8OwFNTm9nCa1+ScnPHmuSnhb9/qUFLCuVkMcf9chPZdSKbG+c8O6sjtRxUZMrXQusFgjYq0WplDNCD9pMQ1UZrqURrjmmoOOpGM6GCo/c0pqrC1GnYrLBnrTFFGjMVVrSbZJW/z112tKVpe6qqRqXTNkui9nXKzPeSFaABZX/Tqapw/dQEGGxnc2xnFyMax91ng9KKaCBGgbqdjmFrPbQ6ot0xwqJwVrqlttqsw7BCnXj3VOlZAwUNnblIr/UtOhQ5/48e/jMRfQX6M0R+DWZN7U4s80l8HYDvgFke7xfExc7BLIpxZEAw4YUZadSskInH4iYUNzn7zF5oP/kUVOO6ybkwABVw2prcU1VhT+fef1CLsD83OB1F4LKsAZjoDj3xGaMX9BQX64nnXzezElNt9pWcoVA6oqJcDSbMFapqinLDTMQ75QTnRaSGZsKFPXP9nd0pqoXp23SjxKSowjKXlUJpw2jvYQK2gftNzT1u5mWcFCVKNG/lQZhkZJK5fBhktoAG+WczzaqIQlPEnm7byBb+pZ1RiZoUlF+jQ0XF0uR3zcq36YVFy7h3menJVvGp/YXOaTht0OYnSSmV1mMSGkQLqtOFxtZ2gtsQQnnDRxyZ4/fq3Ic4V6wwsWssAGacToVQlufZq/pPpQ6CKAMhE/6MzazENbnxHZ3KdrGl4nUZaiHMAISEtr7JHuE3M/4C0WCaIJec75YlrUGN710+IMC8044ak2PyVLaLdeGI+yROwfiV+zp517JGlvkkfp2IfhPAU5n5Zav1b8SIESOOMXg9PgkiuhEm+uh6GEl+CzO/iIgeA5OfNoPhKr6Xmd9mz3kugGfAaEHPZubXNbrHfNOBO4cBeRLMrInouwEcaSFBMBrKjp5iV0/89gwhgelUttsr+Quq4Yz1KWl8zsxEShnLRGOujUY8UyU+Or8WQIjwcPs+uXcKn7YJerv1BHftnfBUzIl8ga18z2vWe3WOXZjPlTZRTz7ahxjbJ42Wf7bKwAuFs3eeAACcKzYx2TI9ZU0oLxbAjq3RsxsW87l4KoM+tSfKesNrcGWZ4cLe1K+OZnI/Qo7ILCt9vwvSXqufWBrOaailzqBEGYUplcitWb+nc5yvZjhfGtrsIVt3e620oDoKHDCuaql1MtzKyrpFW4wiY3xsfQ23VnkbCtRRXkaEFd/1LodtVxSVOz70lX2pcHefnoYU9KSzjC/UtkIspiGJzkaE+WevghVXkKF6St0RyaMKuJUWTRJaoAzvV+zgKksLbqm9iEbTUJG2vywwQN63zAly9wUkllhqlcjfRZS8MfcvrtPx3F1E1SaENbymMrDOJ7EGVAB+kJnfQUTbAN5ORK8H8LMAfpKZ/5CIvtF+/woieiSAbwPwKJg1rt9ARA+/VEuYDk2mez0R/RDMutM7buNRypOooHBvdQJzXSAj7QfHjEJkTkEVSg633CcwUioKMPwsgChCaapKbKoFrspNolChKj+Bni9nUKRxdWEe2f3s//dhCwBwoZ6itseeLTdw58UtLCwddHI6x02nTaTVp4sKd96zDX3GRintZKjOGGGiC4ZaKF8CXE/Cy0JzhT2egmzUjMrD8qF1maGsMly0/ouZoBtmWRnx24ZiElmuACox+Wxle1ERNkdjnCk3cCJb4EHb5j6uyc+HjGMrFCY28myB3Icz+ug0wUXXfmI0E5OkHFKaoWvi6ouMGYou4QCsFloZrRPhEsK8b6H0z2lGpYkSEiGxbj0Et5Snm9ynqsLMjvupKk0YamMtWRvVp+FLwwOWmrHtPKi4FzNyCoL1mdn3pmZq0k1tzyKJUJNCIawaGa4vBUavv6Ljmq0Jj4izrN3zLq1itg6sQ0jYhdXcImvniegDML5ghvH/AoY6+qT9/GQAr2DmPQAfJaIPwyyx8OYDd6YFQ4XEd9n/nyW2Hak8iREjRoy4nFixdtM1RHSr+H6LXTQtAhHdBONIfiuA58BkS/88jH70d+xhNwB4izjtdrvtkmCQkHD5EkcZmgm7ehI5qwBL26iL/nukCQrzNbUa0vWsJY0w14XX2HRy3v3zcyhn5rF+kk6hII1Tubn+6cyU4fCUQLWF3dpYB+fVDIs691FKD9xa4LO2jKH2eSc/hbfkN+G2haG4cF8BtgvTcMHQG2U7XTLPQIvQc80Et4IdgX3lWADWAeqoCh1RF4q4GSxtj90iHUXUXKwLb0k8aHYGD5ic8dbClEpfbmLBsYYra/K47w2qwSGhHFKNNiPprG4vfbEKuqiMVdpM4/8LwD9TlazMI8fwhCpMqYwc97J0hSL2Vu3MWrWmjQo1KZ8sCYRnUXDdsDAUadw/NxFNW2ovclYvuHuaiH4z4ihSrM2a8OcllY2jBdj7nNrJOO+jjmRNqF09jejNdaGTvmzibmZ+XN8BRHQCwKsAPIeZzxHRvwXwL5n5VUT0LTCRSE9E+9veOUjJFFf7dgAPZeafIqIHA7je+TeWYWgV2ALAPwfwBLvpTwH8CjOvf2XxfcK8LCVmVGFT7UWRTDJULwpTlOYr6ShkT5r4pkhfOG+mSv9y7OnCmLW23c1sD4+Y3eGPu7M86f0VNSsUqsS1NnKkoBoXlOHrp6rCNKtwdmGq+149vYDrJ2cAAPfPz6K4rsbOwgiUu8r7AQtzfZrWyArt6SbW5CklngFcEcitdCZqMZEyJcW3CzMZnCjmPkLJTT5dGc9TKrFnTfaCamxncz9ZTlWFB03utfsqZFHRtRC+2Baa6l/4lmgZz21HngvYtpp1uhz6iAU3afYJAYf9CBjZF0eZuS0l0Mgk9py9iNKaqhIzFYTrbj6JwoBdRJ871tFDpkhijaxtLQZqRno9sLgv1IuihX9/SjajuxbXjO4rFe5J/aY0LNgjneY6lIBUYCjEpcn7svIzaE8t1QiJq+tacpTX5LgG/Bz7KgAvY+ZX281PB/D99vPvAPhP9vPtAG4Upz8IgYpqwy/DOMS/CmZRt/P2Wl88pG9DxeBLADzWXuyX7ecrouDfiBEjRlwquDXAl/31wWr6vwbgA8z8QrHrkwD+D/v5qwD8lf38WgDfRkRTInoIgIcB6LMK/jYzPwvA3PSZ7wMw6Tk+wlCfxBcz8xeI7/+DiN419CKXAwqMTWU0oIJqTwcBcbKP1GwKqqPv0lwukUdJd7IdIPOJe5nSkbUyozIkkE2M1nKhMtbCvfUWNnnhLYmrswueCrsmzzFTJXYn5rebqkpQDjU+b+OTOHe9aeeNOsOZu0ykE5cKnGkbumQsBAfWBCrYrGcNIJvUPvdiMqtwYrqH6zZMX07mc2+Ot2lH0XNTNQofmcM4le2G+kF5hW1bD8s9I2c11EyYc7CqJLIW7dHlukhNVdbq8RD0ku6hH1KkVsa6qoP6FeAkvWItoEA71V5FayQSgryjWEPhtNr1z21bzVHmcU0kSXnKfAD5OXLigpBW351Q7Z3VM6o8HbjgvJFsmEaYdVE+bblKoT913O4AajGsx57Qkh3YzubIdHiHveO6hz5bDWvLpn48TIXW9xDRO+22HwfwzwC8iIhymAn+mQDAzO8jolcCeD9MZNSzlkQ2lUSUwT5BIroWGP6iDH1aNRF9NjP/tb3IQ3HE1pXIqca1+XnMaIEdPQ2lgy03CxheEoDnW+c8iczjkjM/GW6pPW+6b6k906adgM/U8YBXCJRKyZlv/9r8HAqq8F5tLMM9XWBGlT/2dLaDOysTvHB1fgElZ5hnZjK4KrsQahmRxoxKfNGJj5l7epDGrTPT5sc+dTX0Xg7YSBUpJJBpFBsViiIkWHFhE/lmC2wVC5zMTcTWVFV+2GioyCehmaARJiZH6zlsqoUXyjNa+PuvoaLJqOTcCwwX7dIWMuoikHzy1SohiwPfWblOQdu+oUjbkImc0cTYkiTmi9m1XM9RIjt6iow0tsg80+1sjvPaKAslZ8jAmImwYqnYFGLilzRRQXHC3ZwnKEj4oKChEYSURByu2vFQWqDQkindlkSXttsmMOQQ7wlFlu+wiXq05dbX6JtYZiUMa4PfhO6n+diOc24GcPPAS7wYpoL3dUR0M4CnAPiJof0bKiR+GMCfENFHYG7mswB859CLjBgxYsRxwxrzJC4Z7Ep0H4UpF/7VMPP3NzHzB4a2MTS66Y+J6GEAHmEv8kEbo3tkUFCN6/MzprwF1bEGxEG7cpoVYDT5e6oT9vMuzuuNyASW5vrpbNfTJwVVOFObXId7qy0UVHvzvKAKO9ZimVCF09kuHjK90xxbnzDtqNK3f7XNr5jrwudaAMB12Xlv1ZTIMOcCp205gS/e+ohfLOmdmw/GR89ehTM7xuGt67AedZZpXH/qnK/BtFNOvPN7a7JATtpHIkko0pHGKK0MALg2Px9p21tqL6KYnPUwt1SF06jrhO5bV8nmIegqIe6w3wXt5ThzeRjSAvKWVOKMNzWQnBOfO52pJi8iw7WZHSdZgbuqbQDAhXqGWVIGxeWrbKm9iHJNEdNNe73WWtezyxIyYekzbDir5b5uq6Ivv6ILM1Va68VY5ltqb+kYWBm8/3FzuWCToX+Bmb8MwAf308Yq5NxjAdxkz/kCIgIz/8Z+Lnop4Ar8bdEi4nQXnPlwv7LOUXLuJ6ctWuC8iILaUntRaKacAGYUKJar1Y5vP8u1vw5go6LgkvdMhu9Nxd0AgBuK+7BFcXhupq0vIyujKJvTImz3nJ5ijsJPsNvZRXzBxt8AMIlPH92+Dn8zvwoAcM/eFuY2Ie/05CJu3LjPh0j+zcWrcOfcCEVTm6kSheRCKGWjxhVpn2hVUG0y10UY5pbai+5rR5T/ljCUBi459pNRW5Pq3d/0Gzg+PnDrimzIZx9F0jIZSoHRdr0aCjP7m1ytdvBJSy+dxSZ29QSb9ruMgpqp0kbdtdeRqqFQWgpxgqqx3/mcFqyb53YmtMXfm1RV4tuLaCXxmUI0lUpCobsoSnM98n68a7NzmHPhlZer1Q7u0Uaxc9GGBwVjPXTTZcAfEdE3A3g1M68sKYeGwP4mgM8G8E4EXwTD1BvZN3pqljwfxmnjik/9ODP/wUGuNWLEiBHrxdFemU7gBwBsAaiIaA4b/M/MJ/tPMxhqSTwOwCP3I4WWoKtmCQD8IjP//NCGFBgzMmUKdrXJeACAGWnvqCqownm9gWszkzQ0F1EOO3qKq7MLnio6rzdw0mrzCzYVYLesJXGnnuBhxV32uAnurLehrPY8Eaa/q/nkNCpXIsRZJBOEVeQySzmU3rmo/eeMtEmKEuPRaXrX52dxdX7B52acqTd9JEwGbXI6RPSLsxb2bGlyJRydbl8GjUKUp5arij2wuM8sNqOCNVZQ5a2gHZ4I57SrldOMceiMnx+IvvIYQyE14gIyQiqxGphaIpVEhE9Hwlek9bY6XWV7cfy//K0/VZ72ltq2muMRk/Bb7+nCB2RsJtVa0/weaalmVIsoshB0AZhx6p7HhKrG4kHps+hE12zRUzVWs70WhYg4/6xF7lIK96xPZzu+jxNUkdXh7mmZ1bgK1j4jXgIw8/ZBzh8qJN4Lo+3fcZCLpeipWbJ6WzDcd8aMHZ74AX9ndRInbc2le+sTmFLpB3wN5V+s83oDcy6832FOwSSdUIUJamxarn+ia//CXZXtmfPYhXuK2jYgnLT0F2Be0i0q/eSvFDBh1xdT9thFusxt5ApgBMaW2vOTf8mZpwqcIHIvx7X5OX/vO3qKHT2Fti/FVfkFlFO7olw9jZbTlHV/jE8iZIZvqj3vDzmtTJHEbTX3fTN9ci91mECzxLfRhlWXFd2vcGijSNK2AoWUUCrppMIhgUyJstd+m08KHMin91BRLmz1jDbLt1yV7eK0Hc9XZTu4Q5/2BS3P1pu+vthVuBApLKlQlutClMisksLRfsBMrGlGeIye3yNRssOz0HbCj9ejMPerkyREjqmnxtXDsVtqz7+/ALBJi+gZOJxU88a2/eJKoJuI6Alt25n5z4acP1RIXAPg/UT0NgBeXWHmJw08fymSmiWPB/B9RPRPAdwKY23c13LOM2Fjh6+/Yf0p9yNGjBjRBeawsNcRxw+LzzOYYoBvxzrWuBZ4/mp9Wg0tNUteAuAFMDrWC2AWPPqu9DxbIOsWAPi8R09ZM6EmwoxKTxtlxDhXm7jyU9kuTqqLmLPRvLbVRWxZR1dGGiXnsTZpP59Wu6ZctqtuQYyF3XctaWyrELsOBCd2RtqUrfDlDjSuUQVur+0qb9HKbBRFuJxWeyicpqVtVVRbyDwD+/NK5Ch1JmLcpTbImFANJbQrd0+b2R40K083zajylJJbvU9aEtdl5/29bau5p8wyMBbIIs3bJxpai6QPB6WdliFQXy0lGRrWRVesftxeJlY+bNab2ofTtYeKMp+1b/NMPcNJa/1+9uROnK03cXdpghE21cJbkZNGomhiSYD9M3Gau9S63e/mqtD6hMjUPOhwYmtQZEXKMjfO2tTps0NszYXz2seQpKIUaVybnxPWdxXl8mRgwFoQad2wg+AKoZv+gfxufcE/O/T8oSGwb+zbT0RvtiFWK6OtZgkzf1rs/1UAv7+0HbjVvRTO65lIKgoRNddnZ6Gh/ODZVAucd8IEGjW0L0Y350Ik5Bn/wMzSTTdkC3zKRhDtco0tqjAXJZXdy+a4+m3lTHeCBuOBdr2FT9bB7wAkYYngiG7KmP2Ek6H0L4dbl0GJl9q9fAqMIgvJe/Kl3VJ78cQuylMXVGFCNa5SISQ3nFdhS5RfT9fwnVHZyYMvw5CM52WOwnQS85ONv9e4nlJ0jlj1TioJcZnreHIz/U4ykFtqhbXx6UOoKFcQ0ieCIfP9vT67gAcW9+FsbcKf55yjsJE7Crr3d1CippZ7HxZoZtxnYLuEaOhRhC76L1lBMK3xJNEoDCgop/7Q3FiobNHCU7I7eoqSch8lOJPU2xpDYa8EuqkFtwP4/KEHrys/fbb8kCa6apYQ0QOsvwIA/iGMT2TEiBEjjgwYy+syHQUQ0b9HEPMKwGMADC6rtC4hsV/R3FWz5Kl26T4GcBuA717WUAZgW1XY1Rk2aeG1qC1a4Jyggmai7HIG9ub5gnMfyZEeN6MKE1EVaJMyr5koANsKOOfoB9bCkqgxoxqFX2ENmHONwjooz+tJZw2jHc6xhUDpZMQovKMxLMoyQwXN1KodzZiww5OgRSaKnNTsTqvmWsbh2cYVYeVKdX7FuhZNbV0rgEV9aSt5IZE8Bh804MuAhD55KspGlnnNm1VEl6RUSdQfNEucBwtEdCbJN0gti5SKChWIm85/N2ZrqnFjcQ8+Xpocmd16il3Y6Dye4Wry64PZMh3O4ompzdquUb5l6cyaKIr8U8KqrYVTX4ucINfOEPTlWoRFh8TvJI7t2r6dXTS12Owzn9ebqEE4ozfsPYT3crMnyXBVXAFsE2D8ug4VgN9i5j8fevK6hMS+0FOzZB85Eewnsy218JN4jSAk5lxglyd+8r9a7Xpz9IzegAL7QEiXmGc+axRiOc0NKnxhvpqd0DAT+hne8C/4JmkUxH5J1JqBbZXh9op8f7o4+ZIzvwRgYbl990JmVHuBAcCWfnbFy5SfpAqqsYWF52BnVKHIxLoE0geSiTU3oA11Ye9jglgAyImhRFpIbthrkwq1ofHmtaAvwjY5iXCTLrHnNSdlQQWJrOeMdMS1R0UFya2MFyilUOLcHiNurVVgAA2hId8CQxUFQVtQ1TpOXETc/fOzAIA7+H7+Hu6qTuLa6QVBKdXexzWHQproWLLykXUzqqGRUHE+bBUNH0oqbM39dguCNrQ+T6AhMBq1o2wfdvQU24VREgFRlNMrM5l4FmtSXviKoZtOM/OL5AYi+v50WxfW5Zq/Ip7UiBEjRqwTbv2WZX+HjKe3bPuOoScPzbjeAnDR1gF5OIDPBfCHYtGhpw294KUCwUi8CTQmpDH1ZZHhndF31ScxowVuKu4BEDuzTquLmHMRJxQ52giMLaW8JaHBOGXzKM6iREEKp22U1F2khQauURB8VNSECLtc45wtD7Asskdq5ZsUF8GeItxfDYo0Q6ltyQgPWbi3JvI5Fl3nFdE+bv2/IN1Jd62CtvPbrAuprab9DrkLwak+6Noubj+xOjrLTwjntXS6tlElTfqr3bKQCYemrHcINjBRaoF6lLgq2/NlXzTMOu+A0azP6ymudcll4ryu5+IrzwqqyVmxO0lQBQBggLXgF1Jq0SOlJefbTpzYbZSlf3YcnPOmyi1wypXpxy52uPDlcxR0FJG3Lhzl6CYieiqA/xPAQ4jotWLXNoB7hrYzlG76MwBfTkT3A/DHMBzXt8IsiQdmPnzHMhm+ugCjZPJD67zO/fKLBVW4Otvxg2QhBue2WqDWhEzU8Xcw7SpsWMGQkcLUfi61xpxrzKw5vkWLeAUwBmYUBv1fldutoYluwnZ9k5Om8UkgWmfB+TnmzJgn9Eq8ZCdjJmrzyAm0pvjFdRPYBHWDVgpCwUbZ+ImRD1Q4bR2rhKX+iT7h0DaptYV3yuNkgqRDvMJhMwku7Iu/Rj6RDq7dCQZ3vEl845bzzTi/ITeC4HT2N/gru8StmxzvsoUoC9SYiYz6FKlfpRS1yNy1utA22bch9fF0RYwtG08h7FVSXTWuygiFjdDaUhpzvugVtD0mP3bXVT/sCqjd9L9gkpWvgUkjcDgP4N1DGxkqJIiZd4noGQD+PTP/LBH95eCujhgxYsRxAwM4wkKCmT8G4GMA9pWe4DBYSBDRl8FYDs9Y8dzLAgIhAwFknM/nbXXTOec+DX8Le34bYCKDtq125ZyAm85ZrWK6ZYMKFGTOu0fvoPBRUJmJWEqoDsBYKptU417LSZ7Xk8aCLw7Lyk3MmbBlx2NBhJpd3Dy10C+BNtFM2FSiLpELdFImmS+sl0yd5rgJCLDnIS7EIK+1TiyjRML3fiuiyzoAkjLfPccBLQ5TCfG4pHZrzutZmyspGdFWzsTVXwpBC2GFuRpkrGF2kXw1HjP9FIB4/APAOT1DaZ26W7TApiqjHB0JuSjPMsoupeW6KDu5yJOj5dLkOn/NHqutmRQY2qiZcULl9rthwifkHOnB4u4vM7Ia1tFUT6HT34ZZngEATgM4w8yPsec8F2YurgE8m5lf19P+lwL49wA+D2bZ0gzAzroL/D0HwHMBvMYunfdQAH8y8NzLAmbGgg0to6OXlnGVMnWHfKijj+LQ3vQMfoOwGltYyQooKMcFbYTNjtY4bwfc1arECcp9ZIiMBNqiGue18qWzZR/aIENN5XKTnh5jZy4Tdp2QSF50Gd3jrhUiPrQ3uWfEKFBj172QrDDxdAA1BIWD84G09R0d+9rQd1zfRB+2tdBGA87rQiO6SaIvM1scn2YLD792EAjp9TNwFL4pk+DSZ67ENqf8bMKV/M58otkcBXbqiY/eK6hHkA3pf0vGuIkJo0QQBP9EmqzokAqMdL98tlLwXJ3toCCFkl3YegYN9spUjfBs1heYvTandGuhU2b+Vn8lol8AcNZ+fiSAbwPwKAAPBPAGInp4zxKm/8Ee/zswxVr/KYDPGdq5VTKu32gd2GDmjwB49tCLjBgxYsSxxBosiZ5Cp+8HfNLxtyDUWnoygFfYhd8+SkQfhqnH9Oaea3yYiDIrSP4zEf2vof0bGt30ZTCZ0ScAPJiIvgDAdzPz9w690OVCycbk93kEUcw6YZtqr0lIh7KzPpy2VVAlLIAyopj2mHBvvWmvN8cjCsKuNprbtZlxJpu2FOZJnRgTidTUoNKEtVST1wyU5HIhljj2RDs1ky+3oMAoWqgkAKgpUEp10ny6mIwp1UC+X6tgFQvioEittmUaa2dEeIPiaKekVB+11Na/jrIZsqRGGsiQoT24ATC/hdOsFcWlXa7Pd71FuUDWSTWl7fb9JqklkzqjnTXR3MdIazt5tFwutR7i52ZQUI0MhMItMMY1FCiqbOve98W66KbV8iSuISKZ1HaLrT0XISl06vDlAD7NzH9lv98A4C1i/+3or569S0QTAO8kop+FEUhbQzs+lG76dwC+DsBrAYCZ39VVfvawQER+EMxFnaOSAyWzrSpMiHCPdt9DgtyCasyoisp6O46+IDYTpx2c59isIQGY9RM+r9jxw3iH4QVD+iJKAeHQ5P/bjWH30tu7HZ7dCva8eJQdy8af4QRAxk0BlQoHdw+ZEDZ7Seb15UIa9gq0h76mz7eTUgJ6tMIWH0VbwcAlaNRP6qBVIoEh6KW2NiQkTagZXpA7ON9UwRpzZN21lBDCuEsbGiwzsLvuq0kvGUHhEYUGdwmp+JmkBRGjCMDkudRg7FpfRMlxyHgRKQudt7I6hsubu5n5cX0HpIVOxa6nAvgteeiKPXkazA/xfQD+JYAbAXzzkE4DKzifmfnjFA+6gxGZI0aMGHHFYz0Sp63Qqd2eA/hHMMtHO9wOM9E7PAjAJzvazQDczMz/BMAcwE+u2rehQuLjRPR3ALA1W54N4AOrXuxSw+ktEyJoDia5S84pmVCTxrXKOQpDKYKMTHKd00ZNIpzTWIwZP9fmvDP1Bs56uinH7fW9uEoZzWjONba8k7FGCcJdtlR5SjM1Kaa4tLb8XLhcCayWJh/XXAoWgHHwc2Q5xQ7/8LmpAYeoEW3zUoY6rvuO60qC66sP1Faeoy8xr0sTT8t2pNfoTqzbH9qopnQspPv9NXvyCOIoLXE9Qb25Wk1tdagAu8iVHcOlfQ9cRNBuz/rQUT9bamV1WhUSLVRs2n4cBRbG01ld+SuU9l7deJ+QtC7XaEqsJ7qJ0FLo1OKJAD7IzLeLba8F8HIieiGM4/phAN7W2j3mmoiuJaIJMy/ajlmGoULiewC8CIb3uh3AHwF41n4ueKnA1txc2B8t4qITmgVRxqZMPAsrxQFhSLvJedcO4F2eRoupf7zaxq6NoNpUFCWaSXTxzGZbYmanfDOAiadKCFq3C5M+GArCfK7Z3J8z50uiEB7rKCj/Ujax4PbJvoveSdF3XF9dp77z+pLE+iZWzd3RXL7tfdBLre20XKetIGJXf9ruY0ifUuqzIO0j8UzCZSAGZqQx51CEcsFZVLRyW4Uw7vM6j0Jmo/73+oD6/T+tz8n6auT7455ZyRl2WPu6TC682xc1hF5bEp0HA1hPdFNroVNm/gOYqCRJNcFGmL4SxrFdAXhWT2QTYIqk/rnNuvZVH1sEUiuGRjfdDZtdPWLEiBEjDNbhA+8pdApm/o6O7TcDuHngJT5p/xRMSY6VMDS66eEAXgLg/sz8+UT0aABPYuZ/u+oFLxWYjZPaJJCF7UajCd93WXkn7ZQ4WgijZPIaV0E6UFEwT9ft29FTHwUFbRakD2bvXCQ+1dFa1UDTehhKJdQgr70vmDH11s1yTSaq2+Ouk3zvO6exj5oRUEOuLbHMApHH7Ic+Ekcu7yP1lB5PsOqa3L3XTR3XA9rebwRYalnXCPW2SlYAhQWwMjDO2MW4dvTUVsU155ooomBhZmDUA2jCZoRYO4XX9it0RQFG7w/VKEWuj6uGHFe7dTTzGrG+4XDJwMw/CZgafMy8s+z4FEPppl+FWSf1V+xF301ELwdwZISEi/jRbDKdJ+IFdIP/jJ7ArExnIiBOqz24X7kE2YHlEpNiDjMjigoCShgTfG6Pjf0MC2QNOqFLaKT7JDSHSCJzTfb/l30vp0DkZ7ATfUzzxOf3vUzu6Tp/RFsklOx7imVROsuOGcr6+ASuZZnDLXEYlyJia7+l1B1WFRJdtKuEG9dOKfpUfQL32JpPNRROq11sZ2GtkXui1RyVX91xW+01+ufvQ1y6N8IsQZsSJd8j175b88LVY6uhrPALV3XvSd9YXRlHuCyHw0FTGIYK1U1mTh0j7fUlRowYMeIzBMTD/g4Z/w4mheEewKQwABicwjDUkribiD4bVh8goqfAZggeFTCMxuqczzKJbUdPAJhEOQ3yi/AoYpxEu8O/ZIW512Jc1If5fm12Dru2zYJqnFa7OG1Xu5IJenNmgJsWRF/S3LLtoX/t+QlNzau9rXvrHKdU1RltJCOYFswNmsr9PxOr1HVhnVaG6+vK5Z73o/Bdxpd7Wan1/dBMQ6wIeaxz8ipo3FufsJ8ZV2dh8aIdPcG92uyrmbCt5t4iKFlFq9/Je0rLxSxD1/Noo2hlm6HkTgXNhb9mCeUX/yoGUJCDwLgi6CbgYCkMQ4XEswDcAuBziegTAD6KI+bIZtjS3+wS4cwz2OE8KhgmMzZLVlhQ4GHl/zXIC5o5ZygoRE48OD/rKasSGWaqwrYNgS2gMGd37awxqNMS3A6rTnpDOH0nIKSZ7YoE7hCjFJNtMzsZPlv1Xl34l3+LaoAD3TSIGuros+tTG/oyuYdGULWdczmS/vpqW3VhHdnmQ+8tnYDTpWg1lC+vP6MShZhPzvMMZ2z4t4LGltrDln0XpI9hlXVG+o7p89u0nSfHs6bKVxsohM9lfaB1RTddahwohWGpkLDJGP+cmZ9oazcpZj6/7+6OGDFixHHBlWFJyBSGTwB4HVZIYVgqJGwyxmPt55U944eNLaows6tz3VObRdGdJeG0HcAtLCMSkaAwt+WWS2QoUON0Nvf7P3di1oS+q7ZaOLvz6t4KrSmGOJlXpWRS7dyt0neXnmIrC+t2d7VpolYIn6gtTadzv7AN0IwXGmoF9SXFpVh2/6ti2fV6FypawfroipLqs+2HVI1NFwVaFXHJju6oMQe3Et52dtHnSABm8aJNtef7sUkLbNtVGeec+7YnqLGgsK60WbFPRNktDSToHp999yd/q4J0RC3JEutrwxUgJA6awjCUbvpLm4jxO4iTMV7dfcrlBaF9EpJFzoA4S7Mv+apkhdKaqjt6al4a+67cVOz40LpNsuXJ7fXmzDij49LgXT6ILoqoa1vfZDkkYuNqtYdP1FP/fYtKsQJa8EHUYHyqzn3UChB8INNkYlGIaSs5RfZNZekL3YYhwqGvjVWLCfa3tZyq2C9lpJGtNHGVkcDoUjLSqLnYd2Qy7OMERqfU3FlvY2oppJPqYtTWjEpcnV3w37fUIoSdQvtV+hQxJlyL9zCsdqeIIx/FurDMB7OyH2sZGFdKdNNDYSyJL4Xp9ZsB/EtbzXsphpJ0V8F4xr8KwD+wf39/5d6uACL6eiL6EBF9mIh+7FJea8SIESP2gyskuunlAF4J4AEwZTx+B0kWdx+GZlx/5766tk9YP8gvAfgamDIgf0FEr2Xm93edw+h2oi4GyMIa8TrGNauo3MCCw1rZH1wUuD43bpnTqkYB8uXBUytiVaSlMSS6LIpV4r6l9bSZUE7yHmTVzwJ1yKGgkLRo2mPMWWG7JYekL2HvoFbEqhbEKpbDkAWNhvQDaC8p7tvspKZW005bLVIO9Y3MtWKrwSzCE6LuMjDu0oaOLTnHlqWUTJQQQVurWibWZb4ERlgP20cwEWOmNM7YKMAJ6s6ku9SicW0B8XhtrErYU05FJ8cOcaDvC4cvAIaAmPk3xff/QkTfN/TkoRnXL27ZfBbArcz8e0MvtgK+BMCHnTlERK+AWWijU0gAYrDJpDEEM1pDmcXnXQlwhIGX1p8pkWHH0i01FCZUe4rpvN7wPO2MLqAg4HxL/RpgWLhr+70MPtSH/rbB3F+gglzdnXvrKc5qxinVne7iolq21MJHRZ3XhE3F0RKQE+jO8suuRhSw2opgioZFOK2TX162FGo4Lp2s2if7VAgsOy+d2Nr61Id03QW5LQOHwngu4s5H9pnKAPfYsFcAPjnURfFF9K1YJc8krXWHY7ty+6Y+lu0fqc5n2xAgaH+vHMqefdG7x6v7cYbgCFgJQ/Anlo15Bcxk8K0A/hsRXQUAzHxv38lDfRIzAJ8LY6YAphb5+wA8g4i+kpmfs4+O9+EGAB8X328H8LfTg4jomQCeCQAPuKF/MI0YMWLE2nEF+CRghAIAfHey/btghMZD+04eKiQ+B8BXMXMFAET0EphKsF8D4D2DuzocbU++IbPtyk63AMDnPXrKC2S2JkwwQ10ehEMNgrIaXE1NLW3hFwzKMGdjKtdMmGSBTsmg/XGagfOII5nW7iAbgK4y34DU8IITXxHbGPJgSfiqt2C7HrbRvmTVzxqEM1r5UtJASDIEjOVwr6Xcrs8q1AglzmV+xRAMScIbHFlFTUd5WrLDleYIZSPCsdHiRonTNxPPIq1KG1sLyXjrWUtbC4dvev0u1FD+eG+VuLEO+IrHmhVq6OjYHZ4YK9te01kQbQ7mtP6Yp6KSwJGCgJm9xlzUUZLnrIJVrUY5D8jrrY16ukKS6Zj5IQc5f6iQuAFmubuz9vsWgAfa8Ni97tP2jcGLaqRwL4ofUCxDOzVqZL1csNuXFgdbcAjnm6nS0001CHPdLiBCzabLO5K6fBYyDHJGFc7riZ/QT6sQMzOz1Jo7tgD7EM576s0oFNid40KAJ6LGVQ3G+8ursUUmRPKqbDcSLn002TL0JeEdNBu7rd6TrO1k1p5oNlNDRQUANVNUYjzi11klkWAqORbJse1BtG0UlbyHNhj/W+aFQm2FghNEM1o06iq1led2cJSSa9uh5LCeA0j7KKiFXe3OJbqtO8pJos1PudbrXQFCwvp4/x6AmyDm/LWWCgfwszDro/4pzCv1BAD/t02ue8MK/R2KvwDwMCJ6CEzyx7cB+D8vwXVGjBgxYt+4QnwS/x/MqnTvwWrGPIDh0U2/RkR/AONQJpgFMZxm/8OrXnTA9SrrfX8dgAzAS5n5ffttz2n0J9UedrjwFIAsG6CIAQ6OsMyWHACCdVIILVh5GqA9omoI9lWDaB+ILAtLOWxRjVJogAUFa2BK7OPkgZh2Oan2ogq7Gml5dvaLu9xWbqHkHPdYa+WM3sRVysTYX51dREFhNTxFIRejOMCbdyktDI+kmTqhhsL5wlZIL92gmuSXJbRUdF43DbWsymrQ+hUmqFHY8ZAR+3ekaGnDWRxy0SIg1tBLVthBs9yNOU9DKeCUpTp3WWHHlt7v0/KH5NZcdlwaf/i68SBmfvR+Tx4a3UQAvhrAQ5n5p4jowUT0JS2VYdcGuyrTH6xyjpv0JTcrYVbgqjC3ty0pJF9j31FKVEEpM7BdUl26/Ki75kEm+8sx6GNT234gwhZVg8KDJbZV1RrFIgWJoxhuzHdwNV/Ex6tTAIA5T3BXbdY8uVefwEOLu73A0Rz8OkVHSfb0XrqwSo0oAKuvHJO2NURoUFBMzL6Yv8/EcqIqEsKqt1bVkHLbXQjjue7k6d349uAgFJwP0HUvfe4lh+WB67RmGTNKq7BsksbMstZndNG60l1b+6tglWKHQ7GuHAgiuhHAbwC4Hkbs3MLML7L7/gWA74NxHv43Zv4Ru/25AJ4B4256NjO/rucSf0hEX8vMf7Sf/g2lm37Zdv6rAPwUjK/2VQC+eD8XHTFixIhjgfX4NyoAP8jM7yCibQBvJ6LXA7g/TOj/o5l5j4iuAwAieiQMBf8omOS4NxDRw3uWMH0LgNcQkYIhSwgAM/PJIZ0bKiT+NjN/ERH9JUzr99lqgkcGPpmOQ/y2gY40vRnVPlGsTJx3GemgmbGob8SuzHiI/mhbyL4LQyq2LjvvINpPqwZmtWenyc+ZfC6Eq/7q61Ell+7ri6OfHLaVxo25iXe4q97yi9ns6CluK6/Cw4u7fR/lok4lUyvtNITeG7KgkUSblbEKPZX5BLAQLNHSovmvJaLOH5+sCQ0Eq0IGW6xSA6sNnm71pWRybGPu34UdzrGtTG0yRym1IUsoV/M5vb/wDqVddeNKI5R72VYV7qrz3jyYVRIUVRsfdADrq4E1WBLMfAfs0gvMfJ6IPgATLPTPAPw0M+/ZfXfaU54M4BV2+0eJ6MMwroA3d1ziFwB8GYD3MK++4OpQIVFaDzkDABFdiyPHxpEZPBSHwLZFoRQ+UzSEvGZENjQwTEK1f4kKIyQcHZINW2+pq1Tyvl7sS01LMfuiXM7Yb3sVO6aA1v65wofbyhVUvOBDK8/Y7N6FF7zxc5L+CqAvrLeJoQKkr430eo0lcVv6EpbSlOelQk1mEIc6RzrNHk4ERpuw6EPfRGraiSsMfKo+6X0S5+sTOG9/n0K5VevssVT5yKk2Wrcte7ptX0bx7+CW4S1Z+fd42T3JZ9GdPR+oq1DgcH0lw1egm64holvF91tsCH/cHtFNAL4QwFsB/ByALyeim2Eczz/EzH8BI0DeIk673W7rwl8BeO9+BAQwXEi8GMBrAFxnO/wUAD+xnwuOGDFixLHB8Gn3bmZ+XN8BRHQChsZ/DjOfI6IcwP1gCvN9MYBX2mJ9g/LIBO4A8KdE9IcAfMrCWkNgmfllRPR2GOc1AfgmZh68aMXlACPQRwo6aCKcAZbGcDVqpPbjnNKaKUrxLyErwmYoRS0jqdG46pmdNWSOUEamon4t2pn/rqqrXPNaltZI08M02kto6IR+UeTWFTf/L9w6xICxAJ1GztzU+BMlqM8RfZQiYNoifxzSMtpDxoqC7rUmllkQoR1GatVcbUvqf7y8GtPavA2btGdK0vjfMkeGkGjXFSTi0FWZ2UTEdZTmSNqU99RlPSwrcaJErs9BnP0ReH3MFREVMALiZaK69u0AXm0tgLcRkQZwDVbPI/uo/ZvYv5XQKyRcbQ+LOyEqBxLRVctqflxOMBNKzmyGLwWTkiqoaIoLdZrmXGBuwzMLqpGRToSBq0ljBq1q4Yy1P6Z9wA/lx9uOW8dk15VE1LY6WdoHGQnlZnoXKutoPFnsr6vPkquXz8us9lfbdsRL3pqoFj+rIbWtDrLg/dDaWQdbp2J12qNtkuyuHTXsAbh+bNp1IfZ0gbutT/N0tosttYfahqguOOusAQU0s7FlX917VxND6xA1tSXCrV0obPCb9N9veo9D1vM4asl0Nnr01wB8INHufxcmWOhPiejhMBP83QBeC+DlRPRCGMf1wwB0Rpoy80/a62ztZ02gZZbE2xFcTg8GcJ/9fBrA3wB4yKoXHDFixIjjgjUl0z0ewNMAvIeI3mm3/TiAlwJ4KRG9F8ACwNOtVfE+InolTMHTCsCzeiKbQERfBiOETgB4MBF9AYDvZubvHdK5XiHhan4Q0X8E8FqbuwAi+gYATxxygcsFE91kyQ/h+FKCCnLar3OanrGRNgYLa4kILSXR0HxOBQWTv21FLAffnwEYYjUM1Tz7yiuvsjqZg2b4JLyaXWXdxJy3X5XQ8tsikSb2d9nhPIqjj/raEgkzxOHcaQmtEauUKJcaa6MCbDTOmtboKhRLl8WwiqVSs8IZu3Lj/Yuz+N8XrwcAbKr7YUayDI2xwAFb/lvUgFq2lnuwBEyQSSg1nvtxWHJujwvvV5flkJb2H3yv+7DgLiWY+U3oTt38Jx3n3Azg5oGX+HcAvg7GAgEzv4uInjC0f0Md11/MzN8jOviHRPSCoRe5HGCQHWAmPFWWDXeD2K30cM4KifP1DDNlTN0iCU1MBYRKyMc0tE7WtpEF43zCUQcOOmDbiq/1txmH7kph0RbZFY5z7XdHMgF26VN7+ZrNqnWpQHHoEqIylDna1oFLUTZ8KPoEQ7q/TTDIY/ZDsaS/9SqTZdRvKD/5P7S4E++48FkAgHft3IjzeoaHTkz0pSshDthkVAo0kixHPkEdTXvSr5eGCtfRZ/Jtt91rp/BcgULK1qT+A7giajcBADN/nCh6Rn0r6kYYOqLuJqKfIKKbiOiziOh5MCvVjRgxYsRnJqzjesjfYYCIvtR+/DgR/R0ATEQTIvohAIMDj4ZaEk8F8G9gwmAZwJ/ZbUcKNdvqllB+YSHFQbPOiLHDeSiJPPDXU6SjxeBrVphbu2TCNTKK8yYKT6lYJ9xAWbyKQ60zLpxjC6ABklqqiLCJyiq353cA8FFGbZFPbeiipYLm2DzbV/EdqKU5bXOVEtBdUTdtGGqhDLEihlgQfZRSG8XSFu3Upln3adA1ExZ2TH+qPoWbZkYHfMNdn4t79k7gwvYMAPCojdtxWu36PpVciCgt9uXI00e54CyyDhTYWxoNWopVdL+p9VBzl3XW/545NiBNDj0QjrYl8csAvgjA98CscX0DTGTUHwF41tBGhobA3gvg+1fv4+WDo5sUaYA13K1J/wFgzF43WAqqe+sEueMMJ9udQBdTTGHU7OqJTx4bikG+iYGUQtudNZKf5ISUrOTVJzSKpMhfBI63y0nY1XWaUY3zOq7Rky5dKfvfR9n5/i8pDich76ltRcNl6I9aGk4xhf6000apcBg6Ybb2K5nQYt+VEtUHFB4xMxGVH9q6Pz509jpM1LUATATUI2Z3AAAKqjzFC8C8Iz6qMJ60F5x5OkvDhKlP3FomiQLWBXe/XYKh7qGfZNHCIWNpCAhXRhVYZr4bwLfv9/xlIbDPZ+bnH/SYESNGjDiWONpC4qFE9Nquncz8pCGNLLMk/i8iOtezn2AKTT1/yMUuJVx0kzFVNdyKazWFUhup9lZQLSIzdKSJKJIrdyl/vD/X6rkF1VH5jRqEXZt7MeccBVW9VTy70KZRtdIKKzprpZPRnC8d2dI6IG9ZGAJPxr8HiqmEKRPu+mHqLcXHys+lPa5su78e7TxdyawtSa2tDMSmDUyYc97QIFNts6F97qPGVrx9mWafWA897bQ5bGUeD9CkW7qun45rZzEHOkbhnsqsd/2EU/8bihh3zU313g/vXuffgwcW95lSHhQsELc4Us0KpSj9UXKe5B2J363FymuznFKkVoT8/dJ3RbMs77+mpY75yFsSd8HUbToQlgmJXwWwPeCYQwfbZB2Tba18Al0pJgdX2C+8JLoRtRRlY9vj56xQE0WLw8/skp5pSOk9ehM7egrAmN/LauB3J0L1C4RlGabhnPaM2BLu5XS1q7R/6XzGuk+mU8hcxjOZ0s4unFgzR9cumSKayWW5A/GaEQtkzbDQVSJzbHekX6lOKL9ttcAZ+1tk4IagkWivsXUwtAm9dUdgNaKbBkT81Mhi/wTHStFE7UUT+lee+gBep/8WAOC+xSZuy64GYOima/PzcApZIS6nQVhwHgm0EN2kbM62Sd7ro3JNW7FQ7Lv/OOJpmNA8EI62kDjPzG88aCPL8iR+8qAXGDFixIjjisOKXBqI29bRyNDopiMPV5ZDwdFNAcre5o6e4upsx684d06rUIbDajM+EkrQT7t6gprI51ScpHlDO3ea6JwL7DrtNdONZKAUfettR997LIdlSUWdtIOk1GxJE7PdRBZl0qEoYtszBRSewjM1nhYtjvuSjcYYSm+Qp5l8tc8WaKhOjbuZMNdsw4UKLOpgOfRZBZmtHNyHVUq1r2o5djmto+sLKmhQH+z9dI0vmWhoLL4QEZghBHQUMOVqPnfLOKv/ZPcR2KnN+L63OoHtbO6rx5rqrR39gRLUU2aOtV3bCjXnllN0Xe9LZx2oS5w7c4QtCWb+R+to5/gICZhBWqM5MGIKKUwcZ+tNz4fWRNjjIiQLURh4ChyFwKZJXlE45UBfgju3sW1gHZ4uwdCccDomW2JbGj1kkYfa/8rSEeGe3T1elVUoQA0Cy+0vWWGehmuKRClfv4eVj3Jp63d6X+G+VynQ1kxKa+vz0tBJ6KVCBhg2gffRiH01iQ6KvradYuUFC6loKdMMOkqic8ft6klj7PU9y7n31Zn/M27/HfvGMzCs1Hfr2FljiXAAZlwfYSGxLhwbITFixIgRlxtH3HG9Fgxd4/rhAF4C4P7M/PlE9GgAT2Lmf3tJe7ciZESE0xpqCmZtjQqfqE7j2uw8ABOZ5JzMADClsuHIBoCZKlFQ5SOaNFMjKW3SUl9rm+Yd2vByzbHNrB5GVQyLm3cx8y7KxFA8It5d4Fq1F51XS0rJlt1wNNLc196Br8/j7q0QJacnVGPBwxaOSZ+N5sxbgH0at+xn23H1YDUw67VeutZkHoohVGKXFpxG5fUhapfj8VtyuEctqKECFRS0p58mWY1K5Le0BQ64fsu+zXWBXW2qVJecY6pKbNpxlUZvuT6k7fY56dNzLhuuACFhq8x+O4CHMvNPEdGDAVzPzJ2VYyWGWhK/CuCHAfwKADDzu4no5QCOlJCQg9LTGlCeRXF+hUwk06WJVM5HIV/8CUrMVBlRTg5hPYSwTQqalF/fbw2eVYTBSitvkWsPmLjPts8zKyw0ZFSSadste1qDMBeFERec+TU6alaYoEZhS1ADIRtdM0XPRmbZpgKgVWDKz+J+o0krPSc5bpXopRA63E91peGcQ7BMQeilEw8wMTbO7ej6jErfx0orT7dmQni49nTSV5dlfV5vRGX4M4QqBo56bO0jpwrCMDq1Dav6dYbgCrEkfhnmNf4qAD8F4DzM2hVfPOTkoU9rs0XqDFvDswNE9HNE9EEiejcRvYaITtvtNxHRRSJ6p/37jwe5zogRI0ZcEjDM1Dvk73Dxt5n5WTBLoIKZ78MKiw8NtSTuJqLPRljj+imwC3cfAK8H8FxmrojoZwA8F8CP2n1/zcyPOWD7AIzG6uosaRCg4SmmLbWHXRU/q9ixGrSUGZeobYkNWVfIaUFutS5J1ThNeSittKzCZZvWKEsppFgasZOUKnD6vrIW2cJaBDvMEZ2UgaF9NJhxRs/FojTus7mGDhFNUN6SMBZIjoXULr0VYJL33L7UwZ2uztaXRNX1TPZLTbjIqbQKcBv2uwLaEOoFCL95l+XYrZ2nlqd7JsL6TtrxuT9ZsBymqkqs93jBrj0u/HmaFaY2OnBbXcRMleFeSHWO1VUtpbU7p3tAWKmSy2GiJKIMYf6+FiuIrqFC4lkAbgHwuUT0CZil8FrrnA8FM/+R+PoWmHWzD4SuAaU9VWJud5fNwFVJJjEgVq3ThZ/sZlSioBrb6qK4ls0chgnnc5PGLFoo3r18+6OV0glhSJ2aIeGU4dh43QknLjUpuxSsjWLhItwv53ZpV5lAl/tERZlApaAx50KUEde+P3MusOA8Fig22mWmSs+Tu3vNomcoQ1vT5zJw/Y4D0wTL6SfD8x+cj2hkhovfuGtMhHO7IuvaKDwXjRYmfjeWz1abjeM3s72oD+k43NFT74c4lV3E6cwUBiwSn9dCULuDIpcO6INZK64MuunFMMVZryOim2Hm2p8YevKgJ8fMH2HmJwK4FsDnMvPfZebb9tHZLnwXgD8U3x9CRH9JRG8koi/vOomInklEtxLRrRfuW62Q3ogRI0YcFMTD/nrbILqRiP6EiD5ARO8jou+3259PRJ8Q1Ps3inOeS0QfJqIPEdHX9bXPzC8D8CMA/h8YBuibmPl3ht7jsgJ/P9Cx3V38hW37xXFvAHB9y67nMfPv2WOeB+PfeJnddweABzPzPUT0WAC/S0SPYuZzaSPMfAuMhYPP+vxt/1PoDqduzUa7c4u8X51fwHZmrIPzdlUuZx5fqGc+rnvXVou9IW/mQ8j1sv31nQVhHbqrJNMNKYPcV6emjdrqy73wlhQBC/tRsStjEu4pWBLmfqX2VyKLqIb4fgJtNaFwXglDS8nznGVTsEu+k/u6HbZxefTLQzek9Y/aoEjvy2JZFrHUV6NpFTqt8z2BisqeLDjzFkFOGlNbkmZTLeIxKj67aKZSm99wq9gTiZsKKl1Pfh+/W2+tpp6xv9byHOuxJCoAP8jM7yCibQBvJ6LX232/yMw/Lw8mokfC1Mx7FMwa128good3LWFq15V4HzP/kv2+TUR/m5nfOqRzy+gmV7fpETCe8Nfa7/8AZk2JXljroxNE9HQAfx/AV9u1W8HMe4BJwWTmtxPRXwN4OIBbe68FWroeg0keI9xR3g+AERLyhdvjwk+Cu/XEvxhTVUXRTim9AnRHTgwNj+yLUAphkMMEQ91DQchnZMqm20gVDpEqrk7TOW3WEJhQ1co7h+vH5Ztd1IqGwqfKU3hgcR+AWOi0tVFa39EMzvfTvO9wn133f3m8hKWgvDr9E/ukm/ruoUlXJtE/A8dF63VbfGKKGbt6Kuo6VThdGNpoRqXxZTnBL0KT22jVmuK+reJLWoa2pVz73oO1gNdTloOZ74D18TLzeSL6AMzaD114MoBX2Lnyo0T0YQBfAuDNHce/BGZdCYedlm2d6H1yzPyTtn7TNQC+iJl/kJl/EMBjATxoyAW6QERfD+OofhIz74rt11onC4jooQAeBuAjB7nWiBEjRlwS8MA/4BpHjdu/Z7Y1R0Q3AfhCAE7L/z4bAfpSIrqf3XYDgI+L025Hv1Ahp4QDALNYcGcAhh74YAAL8X0B4KahF+nAfwAwBfB6S1+9xa6j/QQAP0VEFUyo+/fYRY+WottxnZrnRtu4pzoR5T7MtbAk9MQnDU1VhfsXZyPKxa2TDRh6QFoMMupE9mkZjdBdf6Yvbr5pVretgia3u74B8OayItE3DUCFY0rqdhS7c30FWdIRFXVtfq712cgS7QAw56m3NAqqsaUCPSEd1aEiaHvEmD5gYtv+IK2KNBDCHrGCylkiGxQ9tSxIYahW3XT+U3BG69hC3y7muG5imN/CWpgxLRjTku6+06Q73UHDHqQcSV/V11VWfVwFKxiKdzPz43rbIjoBk7/wHGY+R0QvAfACmLf0BTBlv78L7UFVfT35CBE9G8Z6AIDvxQqK91Ah8ZsA3kZEr7Gd+YcAfmPoRdrAzJ/Tsf1VMA9qtfYwPInMRdvcW5+wpY5NRM3ZehO7tQvZIy8UMmicFJFNJmrDHFdQDeky7zOhZZJZFzpLfi8pe9zFL3cJyHS/EhNDpjQy1v7YORdRCKrLpHZwmeiun/G6FOH6C0G/OEplIYSyExLX5udiPwNx7KvpSkjsCQe+nGgtzc79WdttrQDLk/N6M86XTJppCG28op6d7HUBKKBQ5jc+mc99HScNhXurTf+9FkqRZoUMjJlNpDSRbSJCLhHm6/jN2kuztwiidUY6rSm6iYgKmHnvZcz8agBg5k+L/b8K4Pft19sB3ChOfxCAT/Y0/z0wEU4/YXv8xwBaLZk2DF2+9GYi+kMALtLoO5n5L4deZMSIESOOI9aRcW3LZvwagA/IYCAieoD1VwBGMX+v/fxaAC8nohfCOK4fBqCzxAYz3wnj6N4XhtZuejCAu2Fibf02Zv6b/V54/aCGlrwMJWc4U5v47wkZ5/SeDo9kMzM2wg1T43h1kU9n6q0GzbNKTHZ/5MrqSUVDrYW+Y2rOoBHKnUOHlfjMAjJu8R6jDUs6QVoWXSUyHEqt/L6SM+/4n3Ph+6lZRQa1oydk+0Oe91DNct0oO3IoZKDAqujLxxhyT23UYxfFFB3HKnJIF1SHAARtElJl+ZRSOLELqn30oKSX5iJAZF1YZh2se7EnAOusAvt4AE8D8B4ieqfd9uMAnkpEj7FXuQ3AdwMAM7+PiF4J4P0wkVHP6opsAgAimgF4Bkw01Mx3n/m7hnRuKN303xAexwaAhwD4kL3okUAf3dRWtA8A9nRI9HK8uwvvA4D7FTsAgBuLe7DgHHdVJwHARz2ZtuOV6YAm7z7UVyIxZKLvO37IuemE7p+S9Uk4yIzqDBwlQ+3qacxhi35sqzkUsX82ypadNpcgGyY59ed52sKGYMqIqlQod/ld0kl4WVZy2ud1QkZA+XLyPZNK1zhN2zoo2n4rF/kn9/tr69wL/D2dY8+GhmdKQ658qFmUggdhSjoaY04h2NPFvsbrfnCpflvAZlyvJ7rpTWj3M/xBzzk3A7h54CV+E8AHAXwdTO2mbwfwgaH9G0o3/S35nYi+CFaqjRgxYsRnLK6MjOvPYeZ/TERPZuZft8VZXzf05H2tJ2GTPgZVELxcYKHFAIlW1qOZ+HPs/6fyEAPunNoAcKbeTJLLHP2R5jSIPIRE+1tVmx1iAbRhPxEisvy2slRQoJbyEOlkazV1WTppzSu5INNUlaLqrMKuKNugwCgyl0Rn2t+zz3uuiyV5JOJ6HFs6UmteRUNdtwZaYsDqdj0UTJ+VsV+kz9AlvsnfT4FxoZ56C7vtt2/LfzFrm2vxnihvgcxbcm3WZT0MKb+x35pabSC+IqSEi605Q0SfD+BTWCE6dahP4gfEVwWThHHX0ItcDjDChN+ICBGDQr6oBdX+5XP8+8wW8dtUe37fro1mctSG5HO7THS5T2KViX9opJNp92CTmqKQGaRZQYNRwvkL8qjfuqUPbT6CUufQgnKQ5cdLznC+nvl+T1VI2HNCIaw/0ELbuGslk78J5TVtFklp9871KobUC1rDJKYPMjmtyOGvIlQ0q0i416z871KoGns6rscVL1Gbtf4+bulb+c444SAVCt+HAwrlVYTD2sKkr5yV6W6xORY/AeP0PgHgXw09eaglsS0+VzA+ipXDVEeMGDHiOOEorydBRN/PzC+CiZq6D6ZKxkNXbWeokHh/WhCKiP4xgMFFoi41GIRSZ0EjbtEsnHbVpmVpNuv6+tIUdg1owEQ1DY2KSZ2B0b4e7bttf9y/7sS4vuOGQiE4mKFsVAu1l01fXt4hVMiV+QGlzr114iLJnIa6SQuvke5xgTnnnv6QcHZznJwVIp4UK2SK/bFyHeuIXtlHrorEfiyLSOO+BPRRBEEftiF9frJsR+SA1goX6wlcLu2GKBXuopTkc3XvjyJT1N1hTxcNC6JvTO1nHPe9oxn0JUm0vNQ/4wHxnQBeBODfY2AJjjYMFRLPRVMgtG07NLDlysGORnJmbyIwKKR3ZWAvMDLoaNU6WUtoXVmgfUJhSLhm2zFtNW9WWa3Lg+ET3co6DtUc8sK2hXa64nZyVTd3TxVnjQQ5z1nrIgpFTtvOKH7h06U4tXYUVunDetNj9xtC24b9hNWuOwS0DWnYrHyOaXKfpJhqhJXizpUT7OkcG9nCt+lowILqzvsoAENZipDYviTIIUrQkN+jqwZUNaTW1n5whC0JAB8gottgSoS/W2wnAMzMjx7SyLIqsN8A4BsB3EBELxa7TuKAK9ONGDFixBWNAWXADxPM/FQiuh4mkulJ+21nmSXxSZjqq08C8Hax/TyAf7nfi14KMCPSWpxWnFPtNSpFjIJqT0dkyT5AOF0REr2M+Z13UknLchq6tNa23Ioh1kJrVdSuuk8r0CJS6q/i+FTEorR091sTR81oKAr0RMmZtwDmuoBmEr9J0k6PRllyhnOVyRe6fnrOr4aW9iHVXveT4Nh67CVO1uuzEtNnXyXRda4EPIAofwVwwRg2CEPcw1RVOFtueMtuIyuxSQvbF9UYz67Sq8o0IJzafZTlsvega/zLY1Jrs/83W+NvdISFhMVdAN7DzB/bbwO9QoKZ3wXgXUT0MmY+0pYDg7CnzdKaUUgk8hDBpDT2RDG+mSoxVTaKA3VUz8Zw5ob+SDlbCZkoBjS55jautavwWJ8wSAf9fpPDBk94nYmJLW8FB+6/QreAURTfT6G0L4CnBDXhJqSukNE++u9cNfN9LKge5IdIKZO+iX4VKm8dReX2K+RTmN/ETuBWqKfRXyGrPRT1O1fNsNA5zlvBO1XSb6exp0MdJs2EjSwI5Uipsj5DiSHvQds7EIc1y0TNQB/L5MC0/f1mvacgHG1LAgCYuSaia4howsyL5Wc0sYxueiUzfwuAvyRqPo6hnNaIESNGHEtcGXkSHwPw50T0Wpi1JAAsXzTOYRnd9P32/7+/v75dPjAIlc68NpUmBAHAxdpGXQhN0yUJSdoDQKQhpejTEAvSIorKWRdyRbt27WbVsht9fVhrlctG2+3b3XNXIlCg4XAWL1QNwsVygq3crJNcoPYapCvR3qYZm9+v/d53qilKVrh2cgFAvAgOgM4FmUxdoeEUntm32jNeNTlv7aWto1wSo3Vriq1gh0po/LvVFPMqR2Vrbk1UFZWuuVhPcFE3k+k2Ve7regFAqTOfHNlGFzkMyTeSFkUp6n0Vqkbuo6sMnRbn99h21jWvr2nRocuAT9o/hTidYRCW0U2uAuH3MvOPyn1E9DMwiwYdCWgmXKyLBtcaLdGJpvDo4jKr3nDU7n25qhuhh+4aXaG36bXdOT7yaoBNu6+IpksBVqG/HCc2SipKEaNkFSYkFSan0oartj0vBYqEjSJtQzSBs+UGrpuejyKjnPBvq6flo3mYegX2sgl+UNTNCkJllWi6ob97NIbYjX2XSKqjNUEkjTPLSty7t+H7tEjopYu6wF4dnrejlExEVKCe9nSORUtI86r3IaFZ+fe00hkWOkNu7ylXdePYS4ErQUjYheP2jaEhsF+DpkD4hpZtI0aMGPGZgyuAbSKiP0FLT5n5q4acv8wn8c9hVjF6aBJnuw3gz1fo5yUHA15TOYip3qfFaWEmpw5rB6W749/7HGauzWB1sNfCc1VH39O2OiObkntZtoDNuqDTZxKVRbHPjRmFKKFR69xbEoYWIn9s1BYzILTEc+UmditjSdxvshvVIHLlqkM/OPouNeK2aLX90k3DkvGWWSfDNN+hY91Yce2/iyYdad7yefhx6cYiaX/NPZ1jr869Nq9FxNi8LnBeWNW6w4m8H8jKy56aZAUgWBJK5xG1vI7rtuGoO64tfkh8ngH4ZqyQwrDMkng5gD8E8P8A+DGx/fzQJUUvF5gJCy1f+v2Gx7VDM/mBvqw89dBr9Q1gKRQU5chVGPC58Hu0X7M7SW9IZMey8NdlbTSuKQSq82ko0siIIwoicNVu0unom4bnou+cn8DJYs/vv1jH/PiCTPu5S7AUc6/kttsiYVr57B70Tfy9QmWZwFgD3ZXSsED4XTSpiJaVnys78Xs/nq3lBAQKKYTOiveOgYXe3/oZy+6n7b2ptOnnwq3oR4ZKzpUVGuDO93ffYFwRjmtmfnuy6c+J6I1Dz1/mkzgL4CyApwIAEV0HI4lOENGJo7Xo0IgRI0ZcXlwJlgQRXSW+KgCPBXD90POHVoH9BwDcUnl3AvgsmEUrjsyiQxqEeR3opjZLok2b6kKqrcSOzfjzMkuCk2vKaOK2RYva+p2z9qZ0RSrSkIBubTPte1v7je89Wm8bZdVlETUc9iy2MXXau32as2KKnNwTVXuqZKeedFpOOWXWOdukCVO6Ke1DaiEso4KG0n9Dzhl6zSHtdI3TtppmOzYY4I6dk5GFUDOhtkmmzoqoBDXloqDcvQZrmHvH+tB7SO9HWjHOmpD73XsiabKDVpx1IKzHcU1ENwL4DZiJWwO4xRbmc/t/CMDPAbiWme+2254Ls9pcDeDZzNy3PsTbYewegqGZPmrPHYShjut/C+BLAbyBmb+QiL4S1ro4KmAGFnWgm1gMCDdQM6WXDsCuF0meJyd9w593tCVMXNeGIoYSxzcmIGESNxL07DyRQ/uXcZngk0JimY9CtQgv10a6PXpO3CHs7HbVcr75vPobpkGQpXc28wUW9fJhXNloMUdv5ft8uxtJjfukgtYx6a862XUqC3asyafontO8KpAp7RWweV1gokIZ8Er4IVJKthmtt7p/oE95ksPXXa8WQkqB/XvihMUq114K5nXRTRWAH7Tr9GwDeDsRvZ6Z328FyNcA8KwNET0SZs3qR8Eo7m8good3LWHKzA85SOeGxoWVzHwPAEVEipn/BMBjDnJhIno+EX2CiN5p/75R7HsuEX2YiD5ERF93kOuMGDFixKUC8bC/PjDzHcz8Dvv5PAxLc4Pd/YsAfgRxdNKTAbyCmfeY+aMAPgzgSxp9I/piW7vJff+nRPR7RPTihILqxVBL4gwRnYCpR/4yIroT6ynw94vM/PNyw6pS0sGVCndaAnNTI09zH4bQQA5d2kfahkRbhzWEKd5yjdhK8b2JtGcoG+UDtDrjuvo+1IqStZgacI7njkgreZ02qyO+hlo54koRo4J0bge6o9eqYgCyEmgSLRb3LU6GTLFKEmTbOY19K1gE66JqAGH9gUxUnr0VqYGX/n8bRSSi9xzdFI09QX/2UZ1t/Wjrf9v71VL8wR/ra3NphVK8+6Vu5kStBcObvIaIbhXfb2HmW9KDiOgmAF8I4K1E9CQAn2Dmd1GcQHoDgLeI77cjCBWJXwHwRNvuEwD8NIB/AaPg3wLgKUM6PlRIPBnAHKao37cDOAWzoPalgJeSAD5KRE5KvrnvJGZCWWdmoETUENCRoNsKN5DSgdgnDFJ0DWIgNt36o2HIH1szQVMQIJVWEb0jXw4F9tdfJaqLmaLz+s7t9GU0GkXjODkxy4itPjQmkYTiSPvYdp9dIctt29z9DxFg6QSf+qiGJdodjP7Y7/nymVQcFBEZOurep0KEyDoqalFnvePCnQ8kkU8J0ufFLb9p27Ft75lUDmutULE7tvvdPghWaOpuZn5cb1tGEX8VgOfAKOHPA/C1bYe2bGvrSSaiUL8VRjC9CsCriOidA/s9jG5i5h1mrpm5YuZfZ+YXW/rpoPg+Ino3Eb3ULq8HGIn4cXFMl5QEET2TiG4lolvLs7tr6M6IESNGDATDlCge8rcERFTACIiXMfOrAXw2gIfAFFi9DcCDALzD0ke3A7hRnP4gmLIbKTIicobAVwP4H2LfUANhaTLdebRLKIJZtOLkkvPfgPZQq+cBeAmAF9j2XwDgFwB8F4ZLSVhz7RYA2HrYA7iq49LF6dl92mTos9WmB9qRrVZKH/UzqFUD54Tz3yl8T7WtNg1LEXdqTV2OZrev7/5rNLWxodpzFGkmggrS81OKaiiFFlkWrWuMt/SN2534Q6yOxjUPqNWver11wLfnAyMgyluY/yd2RToXReTOi/IrhEXbdg3u+M0kLVtrBeZuCs5YyuJ7z7vMLCr/8urv9hCswyghwyX9Gswyoy8EAGZ+D4DrxDG3AXgcM99tC/W9nIhcxOnDALytpenfAvBGIrobwEUA/9O29TkwqQ2DsCxPYuViUMn5TxxyHBH9KoDft1+HSsn4Ws4nYdckkJOYG5x+kLb8suF4d35zALZOuC0cvUTNFAuSJea5RIOf1S4MsbmSl2wz8q30vFREHAkbd17dclwDQqCYPg2/D3depXUI5U38CfL6uaA/hiQuVkm28LLz2vomI7aifR1CDegXSqv+1un1hmA//giHhfDnyWUort7cwbm9mY8cnKg6CnOVgqHNJyQnZuffSClhs838X7NCrZth47K9tvGcCgAN00atw7tP/tiup7IPrCe66fEAngbgPYIG+nFm/oP2S/L7iOiVAN4PQ0s9q81ny8w3E9EfA3gAgD9i9p1VML6JQRhscqwbRPQAUUDwHwJ4r/08VEqOGDFixKFiHZYEM78J7QyKPOam5PvNAG4e0PZbWrb971X6d2hCAsDPEtFjYHTS2wB8NzBcSqZgBuq6W8N2xwAAtZRIbot0cpu85tGjFeq+n7jD2qgjLb7n/PRaTN5iSvudWkldmpfc7/eJ/qWWVGdEyYC3pC3HhIihVSjdnT4bknSPMrkhsv+dyY2CDpF0XZv1uAxDndxt/Wjro6SwWi2RFktqP47wIUjbBYDK8U11nFcAALulSa6bZM0qx21968tvKFsoJUlFMYd8hzZF3Y1nRex/VzfO5URh0hhCtNPawbgiCvwdFIcmJJj5aT37BknJFFXdPhBSSsUNPKYw4Pw2MYm5ZU4poXAaFJJrzKKLWqgR2m52cjm14CZUKQx1r3RqCgkJSU21CZPYhA80XNTtFSZfMwH4nqEWUVpSKJD3iWh/nlv7IJ1QZdSMo5dKUcPL30/ybPtCLdt+n6F0VXodGXatiH1iZF/0GDNFQm1IKO4qaBO0Ufay+JEnqsbp6UWcXZiV6eZVHrKYE0GySniuo4PcdikMWHzXuvutICAav5nIUnVU6tD3ZD8gAHQF1G46KA7TkhgxYsSIKxo0IHLpSsexERLORF0WA81MEfmXajAStVWUMtWfeJdur7ld6w4Xarc6pLKTRi8xA5UrO6KDhsRM/SYvxX2VXdKRJRE7AY2VZa8RnR9fbFVFKqIYNEXWintemdKACmsyp4mEgHBSaxWVYqhF/R7prHQ0RF8MvkSfIz3VfB3cM2wLmgj35baH42QuQThRWhbrnYjS/BxquVf3PVcaCoxTk7nf76yjNE9CwuXuuP21+J1cjSVpvaeRTz7YBCFgg5PnTnJsE1Br9k8wfbaM5jt8YIx005UH1gRG8wWIN8B7m9oGjaebEJJI6ta41XZ/gpwklr3bqUBRSGkH839VZ7Fg0IlPIr2PxJcgszXlS2UehfWzKC0S8nwPACT0WuKXSVdtGyKkHbToOxMHAeR8Cva4mhRqNj9CaTU3N1GZkMl0gol6FK6H7qiZoXCTm4yYSym7tqQtQ5okPpKOR7XMz7QuhBpI7ncPv7d79pVWDVqprMMaDvL5t/32TjDUTJ4OdkJB/l5ax6POPwMOVBFbX0YbiABS2o9TIraB+vDXXD94XdFNRxrHSkiMGDFixOXEJZLfRwrHRkgwA7pWjV9NavlkNQvucCBH2gYBdQdflJ7XR+EsQ0rxyL5487xWqCsFlhEfUkOS3RHOeJC51/CdhaZlO26dfVorKKsxGsuhPUHP32fHM6QhN+3vMaZavAWmjIXV5UyW8e/xtZdfqy/+vnlO89jUWknj7xUx2D5H+SyYGFoHGmeVvI11lpGQSIMOnPUQXY9D3SYgHpeloJCAdme8swJqrVA7S0K05TY0ovXarEIO1FPjXgCAsthSvhTGQ+PCx19KHBshAQCs4UdGiFoiQS/B7mvSTc0JgXpezibVFAZn33nNVtIQvtCfYKpXixy6Sia4DkoFCC+/N7l9fwjsno9iT3GZc+BpHnduLAji5+owKOGwZX8amijftcpeQ7ckQrW114i4Cj9Fp89pWTRTFyTHHTaGid98VI12nY8n+m0SdMXxrCJ4V8GqkWlAO23kUAqh4DOsfZRSOn6FT0Inio7sY2PM9z8Llg1R8pzTd/WgYKxlPYmjjmMlJEaMGDHisqJtjd1jhmMkJILmQsQJA5No2q0O62aLqRO89aqCymk2kF43PidytKkkKkYT6sqY+XWpTOhTl6mdRHz4CBpvuTe1ZtYEUgzrDwYp3TyuRfOipB3dsLhackg6ENFNTI0olr4y0Q0HZdRw0lm5rRWp47+ts7Lf7c762lJ0LhqpLfdEd1gSMhGsYZ1dohAaFzTRt7phGhRQ1yqi+qQ1UdcK1Z4Zs9xIXhO/k3bWfaCbOhHRTUsGlmzTUcsh4kIM3v5mVsGYJ3GlwY4RE+YqOeyeU4ZEPfSd7z8JTlVwreZP+jrkYFUgFTcecbK1bVOb737uSPpDsn3FYfVRogblEkVZKvbCjRTFQiHybcR+FkpfxoFohIZyHLmi/f06+kG84KL/DQG2z5e+V5h1URJt4yXyK5H/TYnikExzapO2S8Nm5WTtnnVbX/vGdeN3T/ZJ1C1tpdRcWyQS231OuJfzHDhvpxQm4+9yY1GxGW+AncBX+NGGHOvGpB8Xcjuim17rvD4KiREjRowY0QrGamWdr1AcHyHhIh+sptlnIfRaD10OYU73yXNEko8mkNWIUQPU4pQLmr6IaLIWR5sC6w/pVmJFV6hhnQQLpMWiySzVoOAjnQxlJTX0bs3dP2vnhIyirdp4oGBlcR0otOg+0mcgjDP3zHxgQpslEX3nlm3iXrqwgrM49MVq/JanVpJCTAIaZOs6sST22Y3BWFZ+vM2qaKMFdW2sP14YikmdyVGcN/uqTQbnBLbji5W4f0L8APZ7j5FT2lo6clyI7X5Mi20HBYFHuumKgxUS3DUIOuia+JiWl4WTyT4NO2VAWcFAGp4mIh1HP2RzMs07n4EKl6MWIcSRqS6+CyT5UOZ9U7EwUPNQUz9sN3QTF+5a3Q+FM479HKKv7P5hcf+u26V5Tq7f0dykk2eqGJyJ+6ZwAgcWweyTAkwc5+WPpBqSaDfZicY46Zw7eiQ3EIVUSwFW65h6SmmjtDx9W9tDInFWnfLS9UBSpSka2lYohEgkBW3Dz+jeCSZnFVRp9qlF6AznBM0h5JfS8Suf39AbSH5nSS81vlpBFAkNTsbCOqCPvylxvITEiBEjRlwujHTTFQYGUCqjLDQ5GMBtTh3JPe05rdhpvOSiOhKtn8RgEQoLoIz1kNuVVbM98//iVNStuB1p7bjLZQSdA7pg3y7n5nN2QYFqeC2cKqA8affNzXn5jj2tkhczmrTT7uoNQr1pK5TOFYrzoc16ClQnzD4uGJN7Mn8eK0BPGNkeRffo+kIa0NZa0TlQb4QHV1wwxwCALqhpYVmLiBUEbWGoC68yKg4WgdUcSdIKkVWRWA8tMfTutAht1EiLEcDWzPK5KMTC4kq03vQSjWsKaqrHmujSipdbIM0TucWK1rUC14FiAhPUWTNtTO9SUAvALX9dbQDsZhSGpV6FyRmZu/D32CAlO59Tcn56bAv9RPJ7izV5UIx005WEmqB2MjtpIHqZ/Zhwk33L7xrRPu48Hc4jHe+LqA0CMlf/jACyLw1pOxG677Vpwx2rJ4BIZoWeAPUk9MNNoFw7msV+V/BcfnYRxtwX95TvmH2qhqfgfL8FonfxHMB2eVRC/PIVFwB9Tvlrk0YiFEkI1HAdarmmnNCL3UBB7J1KOxS+GyEhBEZE2QVBx5mN7HK0FcVtxBFb4gKJX4Mbk0k8wXfSFUmEDVOTyulCM+mL2vdFJ6VtDLrUUrBGCEe2QoIW5iFP7s5QOKVjYX5v/+7U4fckbZQSn3yown3I6LvGtdtkaZuQBgBqVGpruRmh2F0KrEFIENGNAH4DZqlnDeAWZn4REb0AwJPttjsBfAczf9Ke81wAz4BhD5/NzK87cEc6cAlW4hgxYsSIzwQwbELP8r9+VAB+kJk/D8CXAngWET0SwM8x86OZ+TEwyzv/awCw+74NwKMAfD2AXyairLXlNeDYWBJUA5P7yNAWiSXhNVv3v9V6I4ujB0xAPjdau4OjjIpd057T+lUdLAdVAapkZKXro9WknFYsNd1UK9TA/CqzcXHaRIvoqen4xh2Zp5DIWjzSepFaPWlu1fL9vXmtLnxma5pLSkkeF1kL9nO4BkfOa0m/cQbUk6BZajH6Judja05qpeU2gIXoSyaem5L9JHAWKA/OhGar4mdsLIsk2oXir20abBqz4DvsH05y/kDtPnaic8++1TDUConqImkykWcASBOy3cyPL87DWHfddEViaS5KqgBmdnGPWEHQcC3v3lDqiTq/xCxBYkGskWGKrrcOS8Iu43yH/XyeiD4A4AZmfr84bAthYDwZwCuYeQ/AR4nowwC+BMCbD9yZFhwbIaFqYHIuUBGetqnDBKanZnIozpvv6eQHxPy5i9rILT0kh8PsXnHtMrw42SIIBbVgqIqRlfZMJyRyO1FmhLown+speR+Aw+adpuPFBYXpJoFVZq8R+qZKNsLItm38APazdkIkfHd9IDfAXehgTtC2XzoLE657Tg5uAg9Cgr2gMgcLocTx+VpeI7ffXXRV5CuIn0N2T7geZ8De6fiYSJjlCEl5GaJ7kIKCVGiD5aTuvovIKLmv3XcQhExvBHB0XvI1nfyGzGodGf2d10kprSiMSQiGijC7M4uOdb+pKiFvN6JF6w1xXG0EBfn1M4TepmJGTSYZNrrftrnlPlsTTSlWnvw4XqPAWGHRoWuI6Fbx/RZmvqXRHtFNAL4QwFvt95sB/FMAZwF8pT3sBgBy7erb7bZLgpFuGjFixIj9YjjddDczP078tQmIEwBeBeA5zHzONM/PY+YbAbwMwPe5Q9t6cmlu8BhZEg7KOlWVpSeklksXzP/OWUwca6Ego6WbDaJRjmkkR+MAglLac98ZqpSftYjwMNqpzu1CLDPlncWA0YLZRvRQHTTyfM7QBSFbmHaMJWE/7zGyvXANVbP/TLUZoP67FvyoRiMyg22/dKHAufL9lCCzgn0411oSrl3j1G73kHNG4CxcQ0+Vp590Jhy+iXXHioKDn4D8U+0U1uKk7YajEzXAoSBSQk1xyCdx1IcsGxF5qhOlPXJ0U3povE+esxI6zJC0Kqo0DkRNJR8p10ZnNvINYKka8rvde6AzGFWyTVNnd55otg67FYR1I/oSfU670WN9LXuETIFqLM6b6zgWQJVNi/HAYKytwB8RFTAC4mXM/OqWQ14O4L8B+DcwlsONYt+DAHxyLR1pwbEREqSBYsdMjIZ+MdtVGXPkgJgosjApu6iZlFpxbUvBQILeURUbWmlhw0crDSrt50UFqrR/U7jIoCe5N6FVRdHEpEFQNjlH1UA1sxNoAUwuGOrK3BOQ7Znjsj0NtdBQC3PDVGqQS/Cp2XwOix80H5ynhoIAyTTbSdU+jFwFWoooOtYnE7n9WQZkgZsxkU92fYWyjo7XswnqrcI+f/K+GkNvMKgKz6ae2sJxlrJyNB3nQXiXJwisE5ZI3rrYJ8NonX/CC+iUMyeEyJw2amTQpNPkz6O9fXNNOnMKFwiIQdYRMDkTuC6nAHm/TyLoOI8nTVbciAL0/aqEolWFUGqqrfLkqcbw2T2/tohAL5Rlf9xP3/McGomjguoibWlfOxayBRAL0PCqrS+3gdvfqRVBphb8rwH4ADO/UGx/GDP/lf36JAAftJ9fC+DlRPRCAA8E8DAAbztwRzpwaEKCiH4bwCPs19MAzjDzYywn9wEAH7L73sLM33P5ezhixIgRS7CePInHA3gagPcQ0Tvtth8H8AwiegSMWPsYgO8xl+T3EdErAbwfJjLqWcxcN1pdEw5NSDDzt7rPRPQLMI4Zh7+2YV+DoRaME7eXnuJRVpunqo7pHnNB8zUT2jK57x1qoSyjrQOFA82gShstGQAtKlDpEhwYUAo8Cd7TBsUjLied3NU07Ch2OKG4BKVl7zVYEjVQ28+VBqq6fSCrhEoyqxzZe6rNffljyd8/eU+krzEOZArIs9COKxPtrI7KWRJV1BfFofYN5yo4rxUBmqGt9VDNMuippalykyDoNVZF2DvtTAJBs9jv/ifXiLTXKL6fYK0ee17DkpAJcmI7+umRCOK67jynkecXTM0uFvkdaRCD3JfbKLt6ZhIdnSVBleibpUiVoE+j6D6R9+NyXUKAAby30kXOSarVB02I7e4a/nadtt5WisM+w6iUGFqOa/kuLX01B6ZnwjEsaDFic++BomX/2Vnka8F6opvehHZ79A96zrkZwM0HvvgAHDrdZE2tbwHwVQdqp2ZMzizMhF0LwSDplhYe3iPdnnKNduJqtslmwkwnTwAoCjOBJkvOhWijMNkTG/7X0ShRVJQb+MLX4M+rGVTrQOPUNWjh+JfKTPi16JOciNOl8NL7c22msd5KAbkdOpnl9u01SHOIiax1fK4WfoAih6xnzUTgwibsWdqpnljBMFX+uVQbhPIEoZqF7kThsAnP3siMF+f4+VQKC3m6n9QENZVMcEShYSb4zHMgrmWkFgiRYYiz3yV7lG4MFFDzHtgqNj5CTFKlOvy571EbnOwTHYh8N5Yyiugm7+My2xwtypk4zl4j8klA7KP4fmOfidgu+kKV8TF4wYDYv0h1eK7ZHiO/yMjngpbdMw9/bUKC2StkxxlHIbrpywF8WnBvAPAQIvpLInojEX1514lE9EwiupWIbi3LnUvf0xEjRoyQWE8y3ZHGJbUkiOgNMKnmKZ7HzL9nPz8VwG+JfXcAeDAz30NEjwXwu0T0KBcSJmHDyG4BgJMnbmBy9IVG5Kz1VoXTuKVmzUJb7otU0BqojJrCVRXaqGsgy0ATq87leUzlaA2qbLmLSoMrLaKNAJqYz7pWoERkRyVCOI5aIkfh1IbqooXpGy1qY0EAQFmaPjuLQGryQFN19s8kfhYsrCMiZc0e6f2r2ttKb0heu6ptJJClSpQStZrIlpl2zvLwLOqJ0ZydQzatldXwKUtjLLUykmPCBsTlIcQ1SBmrwFEuYPjS8KqCiaxzj0aHAIqU4kn70KCwIqdybCWk9yetEq/JW606JHlyoIxSB7Drl4tQS55HWmFe9p9qYHLeUqTnjZUHmDpOQKDJeteCTu83C79vtgDI1gOb3otAG1pk4v5MQIfpS76nofY0soV7TziaE9YCxrh86UHBzE/s209EOYB/BOCx4pw9AHv289uJ6K8BPBzAra2NyOuZZdPM3CQHpYzEkQOE0+/JQGqUkrYTWh5Icc4UoBnsJuZFGR1PWWYoJwAoCtB0AiqNQKFFBeXCTJUyk6KIIvLNMIdIJcB8Tv0Opb1uWfnPvCiBugZLk1hOyuI7lKDFlO23PyWPz0+EYCQwlAr3C0HDAYGaMx2IqDfFDGYX6ZRDF7kXGia00h5XM6imQDmoEA5cT8kUI5yJW0sjaizaMtzThCw3qU7PhMnO+UOCT0Q0YmmZtlBpSgSEFHz+XOkzEP4zGXVnIpYCvcOJYIyFBIdIJKkXuZ8+md8ipUSGsgoB0naee5b5PEzSJiKNvG9NF6Y2Wdu9SyGoMyPYJmfN9+JCXDHA0ErOtyA+1+FZ+/slETEHcU9D/UhDcIVbCUNw2HTTEwF8kJlvdxuI6FpXh4SIHgoT3vWRQ+rfiBEjRnRjpJsuOb4NMdUEAE8A8FNEVMGk5nwPM987qDVFQEZgiNAQrYL9X2RGC5fWgo/o0QCqmIpqtK/CsY46qWG0dUdFlVWkLZMi7+SlyQS0WITvWWb2A4DKmk5uH9TPcV+rKjjMFiW4qsDOkqgqbzmwZrt2taW7FAHCQoCwcoiEBZBaCw0Ht24O/Fa6iUxFVmlNuOtT4jivk5dJOIedgxYwmqXRLoMG6RyRVJk2fO5LLirE2ryIiGJxWr5wzLrrgWyCH2LnsM5tYl/kLHeNxhaKL2vubkk40o11CH8P0nqItGxYilC06xzHnAxVeR/KlmeRFkGImKLeumWuWjEgtPMl9Jw7yP+kbCy84kJL+4llAoTn5J61zlqeKdlu+GPZJxCyrQgbKjfbZyTrcq1bJf4McVwfqpBg5u9o2fYqmMzD1eBMcrcamLCpfZirhpm0pJCIfBdF+F7r+LhaRAmJqBwiBVYqomc8T+neYnse7+2BF4twbELxNKDF9cXEzMKvwnUdzRYsTe4si+guyrIw+WcqFgzuvly/gPAC9AlO21ZoNxORT6opDOR9agbb0FneKKBnZibW0wxaTPBdfgbATCCOfjGyqH3mc0s7RHtdvzS30j8+Csby3QB8aXI/+RPCWhdk2pSRQVEBxYTbT+/D9Ue31BST/ZKF9aJiixwm9WyPGxSThpxQKS3dFH6bjEMRP3vNQEUltBO3P/HU7xEJ/TSyTt4nm+RA5ca6AkgoSzJCTFYlMNUEIN6ZpF0RHjs4bHkIrnArYQgO25IYMWLEiCsXo5C4gsCGbiCt4+imlF5K4c1RqwG6Y3IV4sq1tg5ZEdHkNGdmkC5CAhtzcBRra4FIC4DZOJQ776PdKmhyC5JCmvj7UErFlA4QHMCk0BndVOvYwZ3mSchzhHOa8txYDi6ZTmUxbUUkaiQltFWmDAUImFpRhUuYU9AFie/i8rXTIAU10/Oe+kijRvltRM7g6Iie0txekxXVP2Ntmf35vqw5hAUim3aGTOKAdqXaZaf8/cqOCgvCH8OuTYpYvtSKYYQyHG0VVH30WE1Ru6SpQUFFFpgcs2KsSUvJWP0UP39BLcb3FFNeUel7YTm5Csfps5B1y/yxwyu3LgGP0U1XEkgzst2Fp2UaWdZAawhoVKK6i7Mkiv0FUmC4iJ06ZByTSGwD537y9QX2xOTL6ULq4m32y4i0RSRFnylkQgPdgkAKMJmAl/alLRzYCZo8N4LBhfw6OstdXyWCAAiRZvL5ag41nuwxZGktVdlMeLFOg5u0TJRMaCji3TmeOLpWIfTd65IFtGR/engfjSFpGqYw98uENUtftRagE34G910JuqUzwsdyazHFYz/rdp9EKzVGAGoKwVZK9Mc+X5YUlPMXUHLN5P7SkF5PIYl23XNL1yqJQshlWHgqCLRQEJPowLWAEYWHH1ccGyExYsSIEZcdoyVxBYHZJJQ5LTjNf3Cw8dMO/lNKMaSO5Eb5a2dVwHgandYv8yuUzQUoirAv0d6jq6zCb/atVuboLedsT62VlutxXXcPeJk3UeSxo7rN4S5i/KPvaTdq7ZMAldYga42pMoey5coBU56DPfVE0JmIYBKJV77+UmQ92V2p47VRgyOh1NBODaVlOVKHtPkuaZWW892myHMcNPTIIWsjn+SiUkpoz6pGqDpch8q5ZJ3xEFFD3EX3ZLEzPnXMSxoqcnD7Xcnv3AbmQP05S0FGc7mfpeamBSiOa9RNE5YDaRaLatl3TVLGPqm0u5srYYxuusKRTlASQzIv2377tklUZmy39SHl4WVo6ZKXqhdy4te66QexbXBbuKo7TkIF3wFlmel3YUN1nd8BML4HIvRmU/chiW7yNZ/qUCSRFxVUlnkhkeUqRKi5yU08V1ljyWVrA0ag+FUAU59AOtEnWc29x3YJBfs9NCJoFE4mP/G5rRS9DPGVZdNjAWLqdvl2pJ9EwUQwSd+Nuz9/n+EdIUJcVDAqjS63dwvXOMQXVllz98jJvSeKWwfcc/P9FH4GsGxfx7XZbOWFzlpt68LouB4xYsSIEV1o+BSPIY6VkPBlOUjSTRRrzTI3ItXygdWthfT4VSmjocc3SooISklYDyyiqVDXRpO0/Zefh/XPqJyqyEETW1Mhz42lkYtcjzTfQ7l9iOk3oOk0lHWltHXwA4DKQC5KKg9WBZS1Klyim1LNgIMWRzkrZetBWdqqUKE2VB5bGWniXVRG3D8b+SUdA+KwVAvW4ruI0oGM2BIasHfAyigemQuTJqW5IAe2fZR0lx/j5h1hQZkyESCqo+5rhbjovpsUY9DygaYFIr7L6MTU6rAWgm8vZQXkPrk9ooHXpf0zRkviCkO8YloPzdRGRbkJO6VDAEGttEywjYgoGi440u3p9wFaiqGGOIS9SiGg1+TzkNFTaSJUsjIdmOKkQ3dOW7sNykrwHUoI0Kr2kU+mNlfoA6f0B1LKoSlY/ec0u12E6jJRtMJedD1Jd/X5htowZCy0Tqw9v53om3+kts9SELQdPwQNyqYxTlc4V56/7J7brjf0XWrp19qpJ0epHXMcdu2mESNGjLgiwTCW+5C/PhDRjUT0J0T0ASJ6HxF9v93+c0T0QSJ6NxG9hohOi3OeS0QfJqIPEdHXXcr7PD6WBHMokZ1u70KfFrCMlllHJFJKNzUirFaX4a1XWlWDWuX4tArsZYaJq1+TNtcW9QZEv0NnNFxHO0OvF6EtCGBAKXbqstiW9WlVa2hokMJBsB8Nfdk4WLslsSJ9240KwA8y8zuIaBvA24no9QBeD+C5zFwR0c8AeC6AHyWiR8LUvXsUzBrXbyCih1+qJUyPj5CoNXDu/GH3YsSVjK5J5DPAOTlif+A10E3MfAfMOjpg5vNE9AEANzDzH4nD3gLgKfbzkwG8wi6r8FEi+jCALwHw5gN3pgUj3TRixIgR+wXrYX/ANW4VTfv3zLbmiOgmAF8I4K3Jru8C8If28w0APi723W63XRIcG0viXHXX3f/9zv+4A+Duw+5Lgmsw9mkojmK/xj4Nw5XWp886aOPncd/r3sD/9ZqBh9/NzF/fdwARnYCpgP0cuRInET0PhpJ6mdvUcvol86AfGyHBzNcS0a3M/LjD7ovE2KfhOIr9Gvs0DJ+JfVo26a8CIipgBMTLmPnVYvvTAfx9AF/NoUjW7QBuFKc/CMAn19WXFCPdNGLEiBGHCDILZvwagA8w8wvF9q8H8KMAnsTMu+KU1wL4NiKaEtFDYFbvfNul6t+xsSRGjBgx4grF4wE8DcB7iOiddtuPA3gxgCmA19uFl97CzN/DzO8jolcCeD8MDfWsSxXZBBw/IXHLYXegBWOfhuMo9mvs0zCMfdonmPlNaPcz/EHPOTcDuPmSdUqAeN2xwyNGjBgx4thg9EmMGDFixIhOjEJixIgRI0Z04lgICSL6elvD5MNE9GOH3JfbiOg9RPROIrrVbruKiF5PRH9l/7/fJe7DS4noTiJ6r9jW2YfLUQemo0/PJ6JP2Gf1TiL6xsvcp66aOYf2rHr6dGjPiohmRPQ2InqX7dNP2u2HPaa6+nWo4+rYgZmv6D+YNeH+GsBDAUwAvAvAIw+xP7cBuCbZ9rMAfsx+/jEAP3OJ+/AEAF8E4L3L+gDgkfaZTQE8xD7L7DL16fkAfqjl2MvVpwcA+CL7eRvA/7bXPrRn1dOnQ3tWME7VE/ZzAZMN/KVHYEx19etQx9Vx+zsOlsSXAPgwM3+EmRcAXgFT2+Qo4ckAft1+/nUA33QpL8bMfwbg3oF98HVgmPmjAFwdmMvRpy5crj7dwczvsJ/PA/gATHmDQ3tWPX3qwuXoEzPzBfu1sH+Mwx9TXf3qwmXp13HDcRASl7WOyQAwgD8ioreL+iz3Z1PEC/b/6w6hX119OOzn931kSiG/VNAVl71PSc2cI/GsWur4HNqzIqLMxvDfCeD1zHwknlNHv4AjMq6OA46DkLisdUwG4PHM/EUAvgHAs4joCYfYlyE4zOf3EgCfDeAxMFUwf+Ew+kQdNXPaDm3Zdkn61dKnQ31WzFwz82NgSkB8CRF9fs/hl+05dfTrSIyr44LjICQuax2TZWDmT9r/7wTwGhhz9tNE9AAAsP/feQhd6+rDoT0/Zv60fck1gF9FMP0vW5+ovWbOoT6rtj4dhWdl+3EGwJ8C+HocoTEl+3VUntVxwXEQEn8B4GFE9BAimsAsxvHaw+gIEW2RWTQERLQF4GsBvNf25+n2sKcD+L1D6F5XHy5rHRgJN8FY/EOYZ3XZ+kTUXjMHh/isuvp0mM+KiK4luyoaEW0AeCKAD+KQx1RXvw57XB07HLbnfB1/AL4RJgrkrwE87xD78VCY6Il3AXif6wuAqwH8MYC/sv9fdYn78VswZnYJoz09o68PAJ5nn92HAHzDZezTbwJ4D4B3w7zAD7jMffq7MHTDuwG80/5942E+q54+HdqzAvBoAH9pr/1eAP962bi+TL9fV78OdVwdt7+xLMeIESNGjOjEcaCbRowYMWLEJcIoJEaMGDFiRCdGITFixIgRIzoxCokRI0aMGNGJUUiMGDFixIhOjEJixIgRI0Z0YhQSn0EgogvLj1q5zSeRLc9ORN9ERI/cRxt/SkSPW/H4DxHRk1r23USiHPlxBxH9uPi8YUtjL4jomsPs14jjg1FIjDgQmPm1zPzT9us3wZRjvhz4dma+pJn1RJRdyvbXBC8kmPkimzpGY6mJEWvDKCQ+A0EGP0dE7yWzQNK32u1fYbX0/0pEHySil9kyESCib7Tb3kRELyai37fbv4OI/gMR/R0ATwLwc1ab/WxpIRDRNUR0m/28QUSvsFU6fxvAhujb1xLRm4noHUT0O7bQ3bL7eSyZhWfeDOBZYntm7/Mv7LW+225XRPTLZBaq+X0i+gMieorddxsR/WsiehOAf9zVH3vNN5Kp9vs6UcPo2UT0fnu9V/T0eYtMhdK/IKK/JKIn2+03EdH/tNd7h32uIKIHENGf2Wf7XiL6ciL6aQDOenjZoB9/xIhVcdgp3+Pf5fsDcMH+/80AXg+zYNP9AfwNzGI3XwHgLEzhMwXgzTBlImYwJZYfYs//LQC/bz9/B4D/YD//vwCeIq73pwAeZz9fA+A2+/kHALzUfn40gArA4+wxfwZgy+77UdhSC8l9+Hbt93cD+D/s55+DXdgIwDMB/IT9PAVwK8xiM08B8Af2Hq8HcJ/rN8yiUT8i+tzoD8y6Bf8LwLV2+7eK+/kkgKn9fLrnt/i/AfwTdxxMWZktAJsAZnb7wwDcaj//IEKZlwzAtvxNk7ZvQ7Lw1fg3/u33L8eIz0T8XQC/xcw1TCXPNwL4YgDnALyNmW8HADJ1+m8CcAHAR9gs1AIYIfHMtNEV8AQALwYAZn43Eb3bbv9SGLrqz60BM4ERVJ0golMwk/Eb7abfhCnTDpgCi492VgKAUzAT798F8DtsqoR+ioj+JGn2t5f05xEAPh/A6+32DKYuFWAE1suI6HcB/G5P178WwJOI6Ifs9xmAB8MImf9ARI8BUAN4uN3/FwBeSqZC7O8y8zt72h4xYm0YhcRnJtrq6jvsic81zBjpO74PFQKlOUv2tRUNI5iFY566wjWooy23718w8+uijUR/b0mbO339IaK/BeB9zPxlLef+PRgh+CQA/4qIHsXMVUffvpmZP5S0/XwAnwbwBTDPbg6Ylf3IrE3y9wD8JhH9HDP/xpL7GDHiwBh9Ep+Z+DMA32o5+2thJrW+kskfBPBQMiulAYZeacN5mHWZHW4D8Fj7+Sli+58B+HYAILNIzKPt9rcAeDwRfY7dt0lED0cP2KwjcJaI/q7d9O1i9+sA/HOrfYOIHk6mhPubAHyz9U3cH4Zma0NXfz4E4Foi+jK7vSCiRxGRAnAjM/8JgB+BoZG6fCqvA/AvhM/nC+32UwDusFbO02CsFBDRZwG4k5l/FaaU+BfZ40t3fyNGXAqMQuIzE6+BoUXeBeB/wHDwn+o6mJkvAvheAP/dOnQ/DeO7SPEKAD9sHbGfDeDnYSbp/wXD7zu8BMAJSzP9CKyAYua7YHwcv2X3vQXA5w64n+8E8EvWcX1RbP9PAN4P4B1kwmJ/BcYyehVMuXK37a1t99PVHzZrqT8FwM8Q0btgynn/HZgJ/b8Q0XtgSlj/ohVibXgBjG/j3bZvL7DbfxnA04noLTBUk7NqvgLAO4noL2F8Si+y22+xbYyO6xGXBGOp8BGDQEQnmPmC1Xx/CcBfMfMvHlJf/hTADzHzrQdow93P1TBC6vF9gvJKgo0iexwz333YfRlx5WO0JEYMxT+zjuz3wVAiv3KIfbkXwP9LLcl0K+D37f38TwAvOA4CgmwyHYyFog+5OyOOCUZL4v9vxw5tAAZiIAjapQYHfJWpy8+jPxgpYAaezFcyfKi7r6par/mZmft0D38jEgBE3k0ARCIBQCQSAEQiAUC0AVf9JRdhiYeZAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ds_ave_month.ts.plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "acf885d0-9298-4ad7-b9a1-28901cead816",
+   "metadata": {},
+   "source": [
+    "### 1.2 `weighted=False`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "435f61c7-be19-4e1f-bdee-3c3471378af4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_ave_month_nw = ds.temporal.average(\"ts\", weighted=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "ab0543ba-d8d5-4f70-bb63-44741cfcf2c4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x16472bf70>"
+      ]
+     },
+     "execution_count": 13,
+     "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": [
+    "(ds_ave_month.ts - ds_ave_month_nw.ts).plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "122d2caa-7c89-4bc2-9de9-802c7b33ec56",
+   "metadata": {},
+   "source": [
+    "### 1.3 `center_times=True`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "1bc848e3-3cf0-4460-a8e1-1044839d7561",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_ave_month_center = ds.temporal.average(\"ts\", center_times=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "371b253d-999d-4820-9c10-f48133d04b0e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(145, 192)"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_ave_month_center.ts.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "d207d41b-e09b-4bbc-a77c-84dd229a5b8b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x16480dc10>"
+      ]
+     },
+     "execution_count": 16,
+     "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": [
+    "(ds_ave_month.ts - ds_ave_month_center.ts).plot()  # Just checking there ARE same"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8a1d84d9-5689-4d39-8973-70ccb7fec98e",
+   "metadata": {},
+   "source": [
+    "## 2. Group Average"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e33efc59-649c-4632-b7ba-799043353387",
+   "metadata": {},
+   "source": [
+    "### 2.1 Month"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "1e36edc2-9d01-4881-963a-830859301123",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_gra_month = ds.temporal.group_average(\"ts\", freq=\"month\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "0086e66a-3cd9-4ebe-9d2f-36603d158409",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1872, 145, 192)"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_month.ts.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "2033f778-7196-482c-95ea-fbf8f7d97e68",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x1649d4490>"
+      ]
+     },
+     "execution_count": 19,
+     "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": [
+    "(ds_gra_month.ts[0]-ds.ts[0]).plot()  # Just checking there ARE same"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "5a2c01c9-660b-4592-b270-dddad399df78",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x1649dfe20>"
+      ]
+     },
+     "execution_count": 20,
+     "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": [
+    "(ds_gra_month.ts[-1]-ds.ts[-1]).plot()  # Just checking there ARE same"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6e4b95fb-49e7-4905-82ac-a174d2959d5d",
+   "metadata": {},
+   "source": [
+    "### 2.2 Year"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "477b1c69-08df-48c1-8e6b-77b13d707af1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_gra_year = ds.temporal.group_average(\"ts\", freq=\"year\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "8b199df6-0cbe-4b7d-a336-47628726ee34",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(156, 145, 192)"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_year.ts.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "89a13d86-e4d3-409f-b59a-6aeb685217e5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x164c27e20>"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "(ds_gra_year.ts[-1]-ds.ts[-1]).plot()  # Just checking there are NOT same"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d9583dfb-285f-4bab-8bb7-bea6243af270",
+   "metadata": {},
+   "source": [
+    "### 2.3 Season"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "c478328f-63fd-4a5a-a323-bd3f54c8db24",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_gra_season = ds.temporal.group_average(\"ts\", freq=\"season\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "544c53e0-a676-431a-8a72-84b542ed2874",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(625, 145, 192)"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_season.ts.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "bdf17235-d9eb-450e-b14d-8a11655a9b2e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "}\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:   (lat: 145, bnds: 2, lon: 192, time: 625)\n",
+       "Coordinates:\n",
+       "  * lat       (lat) float64 -90.0 -88.75 -87.5 -86.25 ... 86.25 87.5 88.75 90.0\n",
+       "  * lon       (lon) float64 0.0 1.875 3.75 5.625 7.5 ... 352.5 354.4 356.2 358.1\n",
+       "  * time      (time) datetime64[ns] 1850-01-01 1850-04-01 ... 2006-01-01\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    lat_bnds  (lat, bnds) float64 -90.0 -89.38 -89.38 ... 89.38 89.38 90.0\n",
+       "    lon_bnds  (lon, bnds) float64 -0.9375 0.9375 0.9375 ... 357.2 357.2 359.1\n",
+       "    ts        (time, lat, lon) float32 245.8 245.8 245.8 ... 248.2 248.2 248.2\n",
+       "Attributes: (12/28)\n",
+       "    institution:            CSIRO (Commonwealth Scientific and Industrial Res...\n",
+       "    institute_id:           CSIRO-BOM\n",
+       "    experiment_id:          historical\n",
+       "    source:                 ACCESS1-0 2011. Atmosphere: AGCM v1.0 (N96 grid-p...\n",
+       "    model_id:               ACCESS1-0\n",
+       "    forcing:                GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4...\n",
+       "    ...                     ...\n",
+       "    table_id:               Table Amon (27 April 2011) 9c851218e3842df9a62ef3...\n",
+       "    title:                  ACCESS1-0 model output prepared for CMIP5 historical\n",
+       "    parent_experiment:      pre-industrial control\n",
+       "    modeling_realm:         atmos\n",
+       "    realization:            1\n",
+       "    cmor_version:           2.8.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d6866288-4082-45fc-ad6b-81ca2824270a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d6866288-4082-45fc-ad6b-81ca2824270a' 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'>lat</span>: 145</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lon</span>: 192</li><li><span class='xr-has-index'>time</span>: 625</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-bace03be-6362-479f-ab70-89f480c37933' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bace03be-6362-479f-ab70-89f480c37933' 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'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.75 -87.5 ... 88.75 90.0</div><input id='attrs-44353307-fd49-4e46-ad7e-d10cb46dafce' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-44353307-fd49-4e46-ad7e-d10cb46dafce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a21ba5a2-7867-41c2-87dc-5772359f5c94' class='xr-var-data-in' type='checkbox'><label for='data-a21ba5a2-7867-41c2-87dc-5772359f5c94' 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([-90.  , -88.75, -87.5 , -86.25, -85.  , -83.75, -82.5 , -81.25, -80.  ,\n",
+       "       -78.75, -77.5 , -76.25, -75.  , -73.75, -72.5 , -71.25, -70.  , -68.75,\n",
+       "       -67.5 , -66.25, -65.  , -63.75, -62.5 , -61.25, -60.  , -58.75, -57.5 ,\n",
+       "       -56.25, -55.  , -53.75, -52.5 , -51.25, -50.  , -48.75, -47.5 , -46.25,\n",
+       "       -45.  , -43.75, -42.5 , -41.25, -40.  , -38.75, -37.5 , -36.25, -35.  ,\n",
+       "       -33.75, -32.5 , -31.25, -30.  , -28.75, -27.5 , -26.25, -25.  , -23.75,\n",
+       "       -22.5 , -21.25, -20.  , -18.75, -17.5 , -16.25, -15.  , -13.75, -12.5 ,\n",
+       "       -11.25, -10.  ,  -8.75,  -7.5 ,  -6.25,  -5.  ,  -3.75,  -2.5 ,  -1.25,\n",
+       "         0.  ,   1.25,   2.5 ,   3.75,   5.  ,   6.25,   7.5 ,   8.75,  10.  ,\n",
+       "        11.25,  12.5 ,  13.75,  15.  ,  16.25,  17.5 ,  18.75,  20.  ,  21.25,\n",
+       "        22.5 ,  23.75,  25.  ,  26.25,  27.5 ,  28.75,  30.  ,  31.25,  32.5 ,\n",
+       "        33.75,  35.  ,  36.25,  37.5 ,  38.75,  40.  ,  41.25,  42.5 ,  43.75,\n",
+       "        45.  ,  46.25,  47.5 ,  48.75,  50.  ,  51.25,  52.5 ,  53.75,  55.  ,\n",
+       "        56.25,  57.5 ,  58.75,  60.  ,  61.25,  62.5 ,  63.75,  65.  ,  66.25,\n",
+       "        67.5 ,  68.75,  70.  ,  71.25,  72.5 ,  73.75,  75.  ,  76.25,  77.5 ,\n",
+       "        78.75,  80.  ,  81.25,  82.5 ,  83.75,  85.  ,  86.25,  87.5 ,  88.75,\n",
+       "        90.  ])</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'>0.0 1.875 3.75 ... 356.2 358.1</div><input id='attrs-454f333b-7fec-4467-b04b-27e8c01b1c69' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-454f333b-7fec-4467-b04b-27e8c01b1c69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8a1a1db-a4c1-4fce-b195-82ea63cebe17' class='xr-var-data-in' type='checkbox'><label for='data-b8a1a1db-a4c1-4fce-b195-82ea63cebe17' 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.   ,   1.875,   3.75 ,   5.625,   7.5  ,   9.375,  11.25 ,  13.125,\n",
+       "        15.   ,  16.875,  18.75 ,  20.625,  22.5  ,  24.375,  26.25 ,  28.125,\n",
+       "        30.   ,  31.875,  33.75 ,  35.625,  37.5  ,  39.375,  41.25 ,  43.125,\n",
+       "        45.   ,  46.875,  48.75 ,  50.625,  52.5  ,  54.375,  56.25 ,  58.125,\n",
+       "        60.   ,  61.875,  63.75 ,  65.625,  67.5  ,  69.375,  71.25 ,  73.125,\n",
+       "        75.   ,  76.875,  78.75 ,  80.625,  82.5  ,  84.375,  86.25 ,  88.125,\n",
+       "        90.   ,  91.875,  93.75 ,  95.625,  97.5  ,  99.375, 101.25 , 103.125,\n",
+       "       105.   , 106.875, 108.75 , 110.625, 112.5  , 114.375, 116.25 , 118.125,\n",
+       "       120.   , 121.875, 123.75 , 125.625, 127.5  , 129.375, 131.25 , 133.125,\n",
+       "       135.   , 136.875, 138.75 , 140.625, 142.5  , 144.375, 146.25 , 148.125,\n",
+       "       150.   , 151.875, 153.75 , 155.625, 157.5  , 159.375, 161.25 , 163.125,\n",
+       "       165.   , 166.875, 168.75 , 170.625, 172.5  , 174.375, 176.25 , 178.125,\n",
+       "       180.   , 181.875, 183.75 , 185.625, 187.5  , 189.375, 191.25 , 193.125,\n",
+       "       195.   , 196.875, 198.75 , 200.625, 202.5  , 204.375, 206.25 , 208.125,\n",
+       "       210.   , 211.875, 213.75 , 215.625, 217.5  , 219.375, 221.25 , 223.125,\n",
+       "       225.   , 226.875, 228.75 , 230.625, 232.5  , 234.375, 236.25 , 238.125,\n",
+       "       240.   , 241.875, 243.75 , 245.625, 247.5  , 249.375, 251.25 , 253.125,\n",
+       "       255.   , 256.875, 258.75 , 260.625, 262.5  , 264.375, 266.25 , 268.125,\n",
+       "       270.   , 271.875, 273.75 , 275.625, 277.5  , 279.375, 281.25 , 283.125,\n",
+       "       285.   , 286.875, 288.75 , 290.625, 292.5  , 294.375, 296.25 , 298.125,\n",
+       "       300.   , 301.875, 303.75 , 305.625, 307.5  , 309.375, 311.25 , 313.125,\n",
+       "       315.   , 316.875, 318.75 , 320.625, 322.5  , 324.375, 326.25 , 328.125,\n",
+       "       330.   , 331.875, 333.75 , 335.625, 337.5  , 339.375, 341.25 , 343.125,\n",
+       "       345.   , 346.875, 348.75 , 350.625, 352.5  , 354.375, 356.25 , 358.125])</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'>1850-01-01 ... 2006-01-01</div><input id='attrs-20a5c04d-331e-426f-a142-62366a03c16b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-20a5c04d-331e-426f-a142-62366a03c16b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51260df4-d5fe-4c77-9efe-a01349c4fcb8' class='xr-var-data-in' type='checkbox'><label for='data-51260df4-d5fe-4c77-9efe-a01349c4fcb8' 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;1850-01-01T00:00:00.000000000&#x27;, &#x27;1850-04-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;1850-07-01T00:00:00.000000000&#x27;, ..., &#x27;2005-07-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2005-10-01T00:00:00.000000000&#x27;, &#x27;2006-01-01T00:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-efc65cb9-16d2-4f77-bd95-34e0f6dbcdc9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-efc65cb9-16d2-4f77-bd95-34e0f6dbcdc9' class='xr-section-summary' >Data variables: <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>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'>...</div><input id='attrs-56df24b5-c0bb-42f0-a8a0-4439175dea1d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-56df24b5-c0bb-42f0-a8a0-4439175dea1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-834b384c-82a4-4ee6-a5db-d7f70f9b3a08' class='xr-var-data-in' type='checkbox'><label for='data-834b384c-82a4-4ee6-a5db-d7f70f9b3a08' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-90.   , -89.375],\n",
+       "       [-89.375, -88.125],\n",
+       "       [-88.125, -86.875],\n",
+       "       ...,\n",
+       "       [ 86.875,  88.125],\n",
+       "       [ 88.125,  89.375],\n",
+       "       [ 89.375,  90.   ]])</pre></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'>...</div><input id='attrs-bb9f542c-14ad-4d64-bf1f-bf9f064a285e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bb9f542c-14ad-4d64-bf1f-bf9f064a285e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c819181-c88e-4c50-a44c-33fc0f684a58' class='xr-var-data-in' type='checkbox'><label for='data-8c819181-c88e-4c50-a44c-33fc0f684a58' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ -0.9375,   0.9375],\n",
+       "       [  0.9375,   2.8125],\n",
+       "       [  2.8125,   4.6875],\n",
+       "       ...,\n",
+       "       [353.4375, 355.3125],\n",
+       "       [355.3125, 357.1875],\n",
+       "       [357.1875, 359.0625]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ts</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'>245.8 245.8 245.8 ... 248.2 248.2</div><input id='attrs-b464a8eb-e8d0-4949-bd45-518da09348a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b464a8eb-e8d0-4949-bd45-518da09348a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1bf7109b-d2fb-4e1c-86e1-3c7cd556aa3f' class='xr-var-data-in' type='checkbox'><label for='data-1bf7109b-d2fb-4e1c-86e1-3c7cd556aa3f' 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>operation :</span></dt><dd>temporal_avg</dd><dt><span>mode :</span></dt><dd>group_average</dd><dt><span>freq :</span></dt><dd>season</dd><dt><span>weighted :</span></dt><dd>True</dd><dt><span>center_times :</span></dt><dd>False</dd><dt><span>dec_mode :</span></dt><dd>DJF</dd><dt><span>drop_incomplete_djf :</span></dt><dd>False</dd></dl></div><div class='xr-var-data'><pre>array([[[245.7746 , 245.7746 , 245.7746 , ..., 245.7746 , 245.7746 ,\n",
+       "         245.7746 ],\n",
+       "        [247.9249 , 247.88907, 247.8376 , ..., 248.02216, 248.00014,\n",
+       "         247.9668 ],\n",
+       "        [249.23178, 249.0986 , 248.96024, ..., 249.57938, 249.47083,\n",
+       "         249.35333],\n",
+       "        ...,\n",
+       "        [235.02655, 235.05426, 235.10416, ..., 234.9508 , 234.98038,\n",
+       "         234.99237],\n",
+       "        [235.25314, 235.26389, 235.27103, ..., 235.23233, 235.23886,\n",
+       "         235.24411],\n",
+       "        [235.17322, 235.17322, 235.17322, ..., 235.17322, 235.17322,\n",
+       "         235.17322]],\n",
+       "\n",
+       "       [[216.69006, 216.69006, 216.69006, ..., 216.69006, 216.69006,\n",
+       "         216.69006],\n",
+       "        [221.2711 , 221.17845, 221.0774 , ..., 221.54146, 221.45746,\n",
+       "         221.36563],\n",
+       "        [222.4093 , 222.21126, 222.01859, ..., 222.97116, 222.79462,\n",
+       "         222.60745],\n",
+       "...\n",
+       "        [260.1312 , 260.27594, 260.4571 , ..., 259.6172 , 259.85443,\n",
+       "         259.9823 ],\n",
+       "        [260.9766 , 261.02008, 261.06494, ..., 260.78476, 260.81964,\n",
+       "         260.9129 ],\n",
+       "        [260.44238, 260.44238, 260.44238, ..., 260.44238, 260.44238,\n",
+       "         260.44238]],\n",
+       "\n",
+       "       [[255.0323 , 255.0323 , 255.0323 , ..., 255.0323 , 255.0323 ,\n",
+       "         255.0323 ],\n",
+       "        [255.66856, 255.65044, 255.61559, ..., 255.71199, 255.71211,\n",
+       "         255.70273],\n",
+       "        [256.3542 , 256.28113, 256.23715, ..., 256.52188, 256.4641 ,\n",
+       "         256.40552],\n",
+       "        ...,\n",
+       "        [249.08134, 249.0689 , 249.07765, ..., 249.08594, 249.12238,\n",
+       "         249.12424],\n",
+       "        [248.89888, 248.90686, 248.92628, ..., 248.76369, 248.80582,\n",
+       "         248.8551 ],\n",
+       "        [248.21404, 248.21404, 248.21404, ..., 248.21404, 248.21404,\n",
+       "         248.21404]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-53ce34b6-e500-4c46-9376-26b115d25ad5' class='xr-section-summary-in' type='checkbox'  ><label for='section-53ce34b6-e500-4c46-9376-26b115d25ad5' class='xr-section-summary' >Attributes: <span>(28)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>institution :</span></dt><dd>CSIRO (Commonwealth Scientific and Industrial Research Organisation, Australia), and BOM (Bureau of Meteorology, Australia)</dd><dt><span>institute_id :</span></dt><dd>CSIRO-BOM</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>source :</span></dt><dd>ACCESS1-0 2011. Atmosphere: AGCM v1.0 (N96 grid-point, 1.875 degrees EW x approx 1.25 degree NS, 38 levels); ocean: NOAA/GFDL MOM4p1 (nominal 1.0 degree EW x 1.0 degrees NS, tripolar north of 65N, equatorial refinement to 1/3 degree from 10S to 10 N, cosine dependent NS south of 25S, 50 levels); sea ice: CICE4.1 (nominal 1.0 degree EW x 1.0 degrees NS, tripolar north of 65N, equatorial refinement to 1/3 degree from 10S to 10 N, cosine dependent NS south of 25S); land: MOSES2 (1.875 degree EW x 1.25 degree NS, 4 levels</dd><dt><span>model_id :</span></dt><dd>ACCESS1-0</dd><dt><span>forcing :</span></dt><dd>GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4, CFC11, CFC12, CFC113, HCFC22, HFC125, HFC134a)</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p1</dd><dt><span>branch_time :</span></dt><dd>109207.0</dd><dt><span>contact :</span></dt><dd>The ACCESS wiki: http://wiki.csiro.au/confluence/display/ACCESS/Home. Contact Tony.Hirst@csiro.au regarding the ACCESS coupled climate model. Contact Peter.Uhe@csiro.au regarding ACCESS coupled climate model CMIP5 datasets.</dd><dt><span>history :</span></dt><dd>CMIP5 compliant file produced from raw ACCESS model output using the ACCESS Post-Processor and CMOR2. 2012-01-17T03:16:09Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>references :</span></dt><dd>See http://wiki.csiro.au/confluence/display/ACCESS/ACCESS+Publications</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>3ba59dfe-51df-471d-ae2f-74959d08bd9f</dd><dt><span>version_number :</span></dt><dd>v20120115</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>creation_date :</span></dt><dd>2012-01-17T03:16:09Z</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (27 April 2011) 9c851218e3842df9a62ef38b1e2575bb</dd><dt><span>title :</span></dt><dd>ACCESS1-0 model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>1</dd><dt><span>cmor_version :</span></dt><dd>2.8.0</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:   (lat: 145, bnds: 2, lon: 192, time: 625)\n",
+       "Coordinates:\n",
+       "  * lat       (lat) float64 -90.0 -88.75 -87.5 -86.25 ... 86.25 87.5 88.75 90.0\n",
+       "  * lon       (lon) float64 0.0 1.875 3.75 5.625 7.5 ... 352.5 354.4 356.2 358.1\n",
+       "  * time      (time) datetime64[ns] 1850-01-01 1850-04-01 ... 2006-01-01\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    lat_bnds  (lat, bnds) float64 ...\n",
+       "    lon_bnds  (lon, bnds) float64 ...\n",
+       "    ts        (time, lat, lon) float32 245.8 245.8 245.8 ... 248.2 248.2 248.2\n",
+       "Attributes: (12/28)\n",
+       "    institution:            CSIRO (Commonwealth Scientific and Industrial Res...\n",
+       "    institute_id:           CSIRO-BOM\n",
+       "    experiment_id:          historical\n",
+       "    source:                 ACCESS1-0 2011. Atmosphere: AGCM v1.0 (N96 grid-p...\n",
+       "    model_id:               ACCESS1-0\n",
+       "    forcing:                GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4...\n",
+       "    ...                     ...\n",
+       "    table_id:               Table Amon (27 April 2011) 9c851218e3842df9a62ef3...\n",
+       "    title:                  ACCESS1-0 model output prepared for CMIP5 historical\n",
+       "    parent_experiment:      pre-industrial control\n",
+       "    modeling_realm:         atmos\n",
+       "    realization:            1\n",
+       "    cmor_version:           2.8.0"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_season"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "e6f45b58-4a2b-4142-9d4c-49bf2525cb67",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "season_config_dict = {\"dec_mode\": \"DJF\", \"drop_incomplete_djf\": True}\n",
+    "ds_gra_season2 = ds.temporal.group_average(\"ts\", freq=\"season\", season_config=season_config_dict)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "1eca45d6-04a4-40c5-9d52-0c0adaebfb59",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(623, 145, 192)"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_season2.ts.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "466297d4-4276-4a2e-b17c-c6d158624f52",
+   "metadata": {},
+   "outputs": [
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+       ".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:   (lat: 145, lon: 192, bnds: 2, time: 623)\n",
+       "Coordinates:\n",
+       "  * lat       (lat) float64 -90.0 -88.75 -87.5 -86.25 ... 86.25 87.5 88.75 90.0\n",
+       "  * lon       (lon) float64 0.0 1.875 3.75 5.625 7.5 ... 352.5 354.4 356.2 358.1\n",
+       "  * time      (time) datetime64[ns] 1850-04-01 1850-07-01 ... 2005-10-01\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    lat_bnds  (lat, bnds) float64 -90.0 -89.38 -89.38 ... 89.38 89.38 90.0\n",
+       "    lon_bnds  (lon, bnds) float64 -0.9375 0.9375 0.9375 ... 357.2 357.2 359.1\n",
+       "    ts        (time, lat, lon) float32 216.7 216.7 216.7 ... 260.4 260.4 260.4\n",
+       "Attributes: (12/28)\n",
+       "    institution:            CSIRO (Commonwealth Scientific and Industrial Res...\n",
+       "    institute_id:           CSIRO-BOM\n",
+       "    experiment_id:          historical\n",
+       "    source:                 ACCESS1-0 2011. Atmosphere: AGCM v1.0 (N96 grid-p...\n",
+       "    model_id:               ACCESS1-0\n",
+       "    forcing:                GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4...\n",
+       "    ...                     ...\n",
+       "    table_id:               Table Amon (27 April 2011) 9c851218e3842df9a62ef3...\n",
+       "    title:                  ACCESS1-0 model output prepared for CMIP5 historical\n",
+       "    parent_experiment:      pre-industrial control\n",
+       "    modeling_realm:         atmos\n",
+       "    realization:            1\n",
+       "    cmor_version:           2.8.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-634ddb3b-9d4f-4703-a71a-6ece5cb849ec' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-634ddb3b-9d4f-4703-a71a-6ece5cb849ec' 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'>lat</span>: 145</li><li><span class='xr-has-index'>lon</span>: 192</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>time</span>: 623</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b0f87719-12c9-4509-9290-6fe0c526d7bb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b0f87719-12c9-4509-9290-6fe0c526d7bb' 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'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.75 -87.5 ... 88.75 90.0</div><input id='attrs-236fbc45-e719-4a01-9dc8-dd63b8c40bc2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-236fbc45-e719-4a01-9dc8-dd63b8c40bc2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8cf46a69-2acd-420d-b158-eea0bc65d985' class='xr-var-data-in' type='checkbox'><label for='data-8cf46a69-2acd-420d-b158-eea0bc65d985' 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([-90.  , -88.75, -87.5 , -86.25, -85.  , -83.75, -82.5 , -81.25, -80.  ,\n",
+       "       -78.75, -77.5 , -76.25, -75.  , -73.75, -72.5 , -71.25, -70.  , -68.75,\n",
+       "       -67.5 , -66.25, -65.  , -63.75, -62.5 , -61.25, -60.  , -58.75, -57.5 ,\n",
+       "       -56.25, -55.  , -53.75, -52.5 , -51.25, -50.  , -48.75, -47.5 , -46.25,\n",
+       "       -45.  , -43.75, -42.5 , -41.25, -40.  , -38.75, -37.5 , -36.25, -35.  ,\n",
+       "       -33.75, -32.5 , -31.25, -30.  , -28.75, -27.5 , -26.25, -25.  , -23.75,\n",
+       "       -22.5 , -21.25, -20.  , -18.75, -17.5 , -16.25, -15.  , -13.75, -12.5 ,\n",
+       "       -11.25, -10.  ,  -8.75,  -7.5 ,  -6.25,  -5.  ,  -3.75,  -2.5 ,  -1.25,\n",
+       "         0.  ,   1.25,   2.5 ,   3.75,   5.  ,   6.25,   7.5 ,   8.75,  10.  ,\n",
+       "        11.25,  12.5 ,  13.75,  15.  ,  16.25,  17.5 ,  18.75,  20.  ,  21.25,\n",
+       "        22.5 ,  23.75,  25.  ,  26.25,  27.5 ,  28.75,  30.  ,  31.25,  32.5 ,\n",
+       "        33.75,  35.  ,  36.25,  37.5 ,  38.75,  40.  ,  41.25,  42.5 ,  43.75,\n",
+       "        45.  ,  46.25,  47.5 ,  48.75,  50.  ,  51.25,  52.5 ,  53.75,  55.  ,\n",
+       "        56.25,  57.5 ,  58.75,  60.  ,  61.25,  62.5 ,  63.75,  65.  ,  66.25,\n",
+       "        67.5 ,  68.75,  70.  ,  71.25,  72.5 ,  73.75,  75.  ,  76.25,  77.5 ,\n",
+       "        78.75,  80.  ,  81.25,  82.5 ,  83.75,  85.  ,  86.25,  87.5 ,  88.75,\n",
+       "        90.  ])</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'>0.0 1.875 3.75 ... 356.2 358.1</div><input id='attrs-02584556-7a54-4e3a-b3a4-89508f6156bb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-02584556-7a54-4e3a-b3a4-89508f6156bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f8381ee-3b6b-4512-b651-92746cfb4a1e' class='xr-var-data-in' type='checkbox'><label for='data-5f8381ee-3b6b-4512-b651-92746cfb4a1e' 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.   ,   1.875,   3.75 ,   5.625,   7.5  ,   9.375,  11.25 ,  13.125,\n",
+       "        15.   ,  16.875,  18.75 ,  20.625,  22.5  ,  24.375,  26.25 ,  28.125,\n",
+       "        30.   ,  31.875,  33.75 ,  35.625,  37.5  ,  39.375,  41.25 ,  43.125,\n",
+       "        45.   ,  46.875,  48.75 ,  50.625,  52.5  ,  54.375,  56.25 ,  58.125,\n",
+       "        60.   ,  61.875,  63.75 ,  65.625,  67.5  ,  69.375,  71.25 ,  73.125,\n",
+       "        75.   ,  76.875,  78.75 ,  80.625,  82.5  ,  84.375,  86.25 ,  88.125,\n",
+       "        90.   ,  91.875,  93.75 ,  95.625,  97.5  ,  99.375, 101.25 , 103.125,\n",
+       "       105.   , 106.875, 108.75 , 110.625, 112.5  , 114.375, 116.25 , 118.125,\n",
+       "       120.   , 121.875, 123.75 , 125.625, 127.5  , 129.375, 131.25 , 133.125,\n",
+       "       135.   , 136.875, 138.75 , 140.625, 142.5  , 144.375, 146.25 , 148.125,\n",
+       "       150.   , 151.875, 153.75 , 155.625, 157.5  , 159.375, 161.25 , 163.125,\n",
+       "       165.   , 166.875, 168.75 , 170.625, 172.5  , 174.375, 176.25 , 178.125,\n",
+       "       180.   , 181.875, 183.75 , 185.625, 187.5  , 189.375, 191.25 , 193.125,\n",
+       "       195.   , 196.875, 198.75 , 200.625, 202.5  , 204.375, 206.25 , 208.125,\n",
+       "       210.   , 211.875, 213.75 , 215.625, 217.5  , 219.375, 221.25 , 223.125,\n",
+       "       225.   , 226.875, 228.75 , 230.625, 232.5  , 234.375, 236.25 , 238.125,\n",
+       "       240.   , 241.875, 243.75 , 245.625, 247.5  , 249.375, 251.25 , 253.125,\n",
+       "       255.   , 256.875, 258.75 , 260.625, 262.5  , 264.375, 266.25 , 268.125,\n",
+       "       270.   , 271.875, 273.75 , 275.625, 277.5  , 279.375, 281.25 , 283.125,\n",
+       "       285.   , 286.875, 288.75 , 290.625, 292.5  , 294.375, 296.25 , 298.125,\n",
+       "       300.   , 301.875, 303.75 , 305.625, 307.5  , 309.375, 311.25 , 313.125,\n",
+       "       315.   , 316.875, 318.75 , 320.625, 322.5  , 324.375, 326.25 , 328.125,\n",
+       "       330.   , 331.875, 333.75 , 335.625, 337.5  , 339.375, 341.25 , 343.125,\n",
+       "       345.   , 346.875, 348.75 , 350.625, 352.5  , 354.375, 356.25 , 358.125])</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'>1850-04-01 ... 2005-10-01</div><input id='attrs-60bc19f8-d3a1-4a0a-8d4c-10cec06bd0c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-60bc19f8-d3a1-4a0a-8d4c-10cec06bd0c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc144f46-d341-473e-91ae-24ea1cea3803' class='xr-var-data-in' type='checkbox'><label for='data-fc144f46-d341-473e-91ae-24ea1cea3803' 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;1850-04-01T00:00:00.000000000&#x27;, &#x27;1850-07-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;1850-10-01T00:00:00.000000000&#x27;, ..., &#x27;2005-04-01T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2005-07-01T00:00:00.000000000&#x27;, &#x27;2005-10-01T00:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7e4c4c81-e023-4365-bc11-17da1dee316d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7e4c4c81-e023-4365-bc11-17da1dee316d' class='xr-section-summary' >Data variables: <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>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'>...</div><input id='attrs-1bf5477b-1f97-4d09-8ab4-07178e850b69' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1bf5477b-1f97-4d09-8ab4-07178e850b69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a09bdaa3-d1dc-4daa-afa7-f7136157d8be' class='xr-var-data-in' type='checkbox'><label for='data-a09bdaa3-d1dc-4daa-afa7-f7136157d8be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-90.   , -89.375],\n",
+       "       [-89.375, -88.125],\n",
+       "       [-88.125, -86.875],\n",
+       "       ...,\n",
+       "       [ 86.875,  88.125],\n",
+       "       [ 88.125,  89.375],\n",
+       "       [ 89.375,  90.   ]])</pre></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'>...</div><input id='attrs-41cda811-0216-4fca-9c5d-0a5c15aa2f7b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-41cda811-0216-4fca-9c5d-0a5c15aa2f7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-74685fd1-bda0-4d2f-863f-36e3fff8ba0c' class='xr-var-data-in' type='checkbox'><label for='data-74685fd1-bda0-4d2f-863f-36e3fff8ba0c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ -0.9375,   0.9375],\n",
+       "       [  0.9375,   2.8125],\n",
+       "       [  2.8125,   4.6875],\n",
+       "       ...,\n",
+       "       [353.4375, 355.3125],\n",
+       "       [355.3125, 357.1875],\n",
+       "       [357.1875, 359.0625]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ts</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'>216.7 216.7 216.7 ... 260.4 260.4</div><input id='attrs-a011cbc4-c38a-4589-bbd9-fa597e141857' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a011cbc4-c38a-4589-bbd9-fa597e141857' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f57b98e-4d06-40a7-ae0e-6adf1da71b3a' class='xr-var-data-in' type='checkbox'><label for='data-4f57b98e-4d06-40a7-ae0e-6adf1da71b3a' 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>operation :</span></dt><dd>temporal_avg</dd><dt><span>mode :</span></dt><dd>group_average</dd><dt><span>freq :</span></dt><dd>season</dd><dt><span>weighted :</span></dt><dd>True</dd><dt><span>center_times :</span></dt><dd>False</dd><dt><span>dec_mode :</span></dt><dd>DJF</dd><dt><span>drop_incomplete_djf :</span></dt><dd>True</dd></dl></div><div class='xr-var-data'><pre>array([[[216.69006, 216.69006, 216.69006, ..., 216.69006, 216.69006,\n",
+       "         216.69006],\n",
+       "        [221.2711 , 221.17845, 221.0774 , ..., 221.54146, 221.45746,\n",
+       "         221.36563],\n",
+       "        [222.4093 , 222.21126, 222.01859, ..., 222.97116, 222.79462,\n",
+       "         222.60745],\n",
+       "        ...,\n",
+       "        [252.47852, 252.54172, 252.60825, ..., 252.26718, 252.33838,\n",
+       "         252.40701],\n",
+       "        [252.24442, 252.27109, 252.30112, ..., 252.16464, 252.18777,\n",
+       "         252.21985],\n",
+       "        [251.60664, 251.60664, 251.60664, ..., 251.60664, 251.60664,\n",
+       "         251.60664]],\n",
+       "\n",
+       "       [[208.37415, 208.37415, 208.37415, ..., 208.37415, 208.37415,\n",
+       "         208.37415],\n",
+       "        [214.52219, 214.47375, 214.43298, ..., 214.62953, 214.59229,\n",
+       "         214.55405],\n",
+       "        [216.02771, 215.94063, 215.85844, ..., 216.31018, 216.22244,\n",
+       "         216.12088],\n",
+       "...\n",
+       "        [272.2145 , 272.20975, 272.2072 , ..., 272.22623, 272.21893,\n",
+       "         272.2175 ],\n",
+       "        [272.19614, 272.19522, 272.19733, ..., 272.1866 , 272.19006,\n",
+       "         272.1986 ],\n",
+       "        [272.14172, 272.14172, 272.14172, ..., 272.14172, 272.14172,\n",
+       "         272.14172]],\n",
+       "\n",
+       "       [[226.63501, 226.63501, 226.63501, ..., 226.63501, 226.63501,\n",
+       "         226.63501],\n",
+       "        [229.93898, 229.88812, 229.82063, ..., 230.1015 , 230.04771,\n",
+       "         229.99788],\n",
+       "        [230.81123, 230.66733, 230.51959, ..., 231.22829, 231.09572,\n",
+       "         230.9584 ],\n",
+       "        ...,\n",
+       "        [260.1312 , 260.27594, 260.4571 , ..., 259.6172 , 259.85443,\n",
+       "         259.9823 ],\n",
+       "        [260.9766 , 261.02008, 261.06494, ..., 260.78476, 260.81964,\n",
+       "         260.9129 ],\n",
+       "        [260.44238, 260.44238, 260.44238, ..., 260.44238, 260.44238,\n",
+       "         260.44238]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b5e7fd5a-0c82-4eec-a41b-f9e2f2c42882' class='xr-section-summary-in' type='checkbox'  ><label for='section-b5e7fd5a-0c82-4eec-a41b-f9e2f2c42882' class='xr-section-summary' >Attributes: <span>(28)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>institution :</span></dt><dd>CSIRO (Commonwealth Scientific and Industrial Research Organisation, Australia), and BOM (Bureau of Meteorology, Australia)</dd><dt><span>institute_id :</span></dt><dd>CSIRO-BOM</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>source :</span></dt><dd>ACCESS1-0 2011. Atmosphere: AGCM v1.0 (N96 grid-point, 1.875 degrees EW x approx 1.25 degree NS, 38 levels); ocean: NOAA/GFDL MOM4p1 (nominal 1.0 degree EW x 1.0 degrees NS, tripolar north of 65N, equatorial refinement to 1/3 degree from 10S to 10 N, cosine dependent NS south of 25S, 50 levels); sea ice: CICE4.1 (nominal 1.0 degree EW x 1.0 degrees NS, tripolar north of 65N, equatorial refinement to 1/3 degree from 10S to 10 N, cosine dependent NS south of 25S); land: MOSES2 (1.875 degree EW x 1.25 degree NS, 4 levels</dd><dt><span>model_id :</span></dt><dd>ACCESS1-0</dd><dt><span>forcing :</span></dt><dd>GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4, CFC11, CFC12, CFC113, HCFC22, HFC125, HFC134a)</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p1</dd><dt><span>branch_time :</span></dt><dd>109207.0</dd><dt><span>contact :</span></dt><dd>The ACCESS wiki: http://wiki.csiro.au/confluence/display/ACCESS/Home. Contact Tony.Hirst@csiro.au regarding the ACCESS coupled climate model. Contact Peter.Uhe@csiro.au regarding ACCESS coupled climate model CMIP5 datasets.</dd><dt><span>history :</span></dt><dd>CMIP5 compliant file produced from raw ACCESS model output using the ACCESS Post-Processor and CMOR2. 2012-01-17T03:16:09Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>references :</span></dt><dd>See http://wiki.csiro.au/confluence/display/ACCESS/ACCESS+Publications</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>3ba59dfe-51df-471d-ae2f-74959d08bd9f</dd><dt><span>version_number :</span></dt><dd>v20120115</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>creation_date :</span></dt><dd>2012-01-17T03:16:09Z</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (27 April 2011) 9c851218e3842df9a62ef38b1e2575bb</dd><dt><span>title :</span></dt><dd>ACCESS1-0 model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>1</dd><dt><span>cmor_version :</span></dt><dd>2.8.0</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:   (lat: 145, lon: 192, bnds: 2, time: 623)\n",
+       "Coordinates:\n",
+       "  * lat       (lat) float64 -90.0 -88.75 -87.5 -86.25 ... 86.25 87.5 88.75 90.0\n",
+       "  * lon       (lon) float64 0.0 1.875 3.75 5.625 7.5 ... 352.5 354.4 356.2 358.1\n",
+       "  * time      (time) datetime64[ns] 1850-04-01 1850-07-01 ... 2005-10-01\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    lat_bnds  (lat, bnds) float64 ...\n",
+       "    lon_bnds  (lon, bnds) float64 ...\n",
+       "    ts        (time, lat, lon) float32 216.7 216.7 216.7 ... 260.4 260.4 260.4\n",
+       "Attributes: (12/28)\n",
+       "    institution:            CSIRO (Commonwealth Scientific and Industrial Res...\n",
+       "    institute_id:           CSIRO-BOM\n",
+       "    experiment_id:          historical\n",
+       "    source:                 ACCESS1-0 2011. Atmosphere: AGCM v1.0 (N96 grid-p...\n",
+       "    model_id:               ACCESS1-0\n",
+       "    forcing:                GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4...\n",
+       "    ...                     ...\n",
+       "    table_id:               Table Amon (27 April 2011) 9c851218e3842df9a62ef3...\n",
+       "    title:                  ACCESS1-0 model output prepared for CMIP5 historical\n",
+       "    parent_experiment:      pre-industrial control\n",
+       "    modeling_realm:         atmos\n",
+       "    realization:            1\n",
+       "    cmor_version:           2.8.0"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_season2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "a696b1c5-5a02-4e2e-80aa-66ba4f2f7a50",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x164d4e520>"
+      ]
+     },
+     "execution_count": 30,
+     "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": [
+    "(ds_gra_season.ts[-1]-ds_gra_season2.ts[-1]).plot()  # Just checking there are NOT same"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "15adc8db-a9de-4ccb-bb34-b31e4f7fedd5",
+   "metadata": {},
+   "source": [
+    "### 2.4 Day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "ef6ab42f-c91b-4049-bd22-a027db7ea9a1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_gra_day = ds.temporal.group_average(\"ts\", freq=\"day\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "735e7f9d-c35e-481f-9639-c698acf6618a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1872, 145, 192)"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_day.ts.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "b6bac77b-8a88-4c77-8d26-ee0a2470c05c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
+       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
+       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=dark],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1F1F1F;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-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.DataArray &#x27;ts&#x27; (lat: 145, lon: 192)&gt;\n",
+       "array([[0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       ...,\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)\n",
+       "Coordinates:\n",
+       "  * lat      (lat) float64 -90.0 -88.75 -87.5 -86.25 ... 86.25 87.5 88.75 90.0\n",
+       "  * lon      (lon) float64 0.0 1.875 3.75 5.625 7.5 ... 352.5 354.4 356.2 358.1</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'ts'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 145</li><li><span class='xr-has-index'>lon</span>: 192</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-23d054b9-d8e0-4bfc-9bbe-f774df7ca80f' class='xr-array-in' type='checkbox' checked><label for='section-23d054b9-d8e0-4bfc-9bbe-f774df7ca80f' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0</span></div><div class='xr-array-data'><pre>array([[0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       ...,\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-dcec337d-95b2-4bbc-a010-82866860cfa6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-dcec337d-95b2-4bbc-a010-82866860cfa6' class='xr-section-summary' >Coordinates: <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 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'>-90.0 -88.75 -87.5 ... 88.75 90.0</div><input id='attrs-be621a41-c930-47b1-bcc4-de25a223b26c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be621a41-c930-47b1-bcc4-de25a223b26c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3299aea-be58-4289-8d3e-b5af9cc5bad1' class='xr-var-data-in' type='checkbox'><label for='data-a3299aea-be58-4289-8d3e-b5af9cc5bad1' 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([-90.  , -88.75, -87.5 , -86.25, -85.  , -83.75, -82.5 , -81.25, -80.  ,\n",
+       "       -78.75, -77.5 , -76.25, -75.  , -73.75, -72.5 , -71.25, -70.  , -68.75,\n",
+       "       -67.5 , -66.25, -65.  , -63.75, -62.5 , -61.25, -60.  , -58.75, -57.5 ,\n",
+       "       -56.25, -55.  , -53.75, -52.5 , -51.25, -50.  , -48.75, -47.5 , -46.25,\n",
+       "       -45.  , -43.75, -42.5 , -41.25, -40.  , -38.75, -37.5 , -36.25, -35.  ,\n",
+       "       -33.75, -32.5 , -31.25, -30.  , -28.75, -27.5 , -26.25, -25.  , -23.75,\n",
+       "       -22.5 , -21.25, -20.  , -18.75, -17.5 , -16.25, -15.  , -13.75, -12.5 ,\n",
+       "       -11.25, -10.  ,  -8.75,  -7.5 ,  -6.25,  -5.  ,  -3.75,  -2.5 ,  -1.25,\n",
+       "         0.  ,   1.25,   2.5 ,   3.75,   5.  ,   6.25,   7.5 ,   8.75,  10.  ,\n",
+       "        11.25,  12.5 ,  13.75,  15.  ,  16.25,  17.5 ,  18.75,  20.  ,  21.25,\n",
+       "        22.5 ,  23.75,  25.  ,  26.25,  27.5 ,  28.75,  30.  ,  31.25,  32.5 ,\n",
+       "        33.75,  35.  ,  36.25,  37.5 ,  38.75,  40.  ,  41.25,  42.5 ,  43.75,\n",
+       "        45.  ,  46.25,  47.5 ,  48.75,  50.  ,  51.25,  52.5 ,  53.75,  55.  ,\n",
+       "        56.25,  57.5 ,  58.75,  60.  ,  61.25,  62.5 ,  63.75,  65.  ,  66.25,\n",
+       "        67.5 ,  68.75,  70.  ,  71.25,  72.5 ,  73.75,  75.  ,  76.25,  77.5 ,\n",
+       "        78.75,  80.  ,  81.25,  82.5 ,  83.75,  85.  ,  86.25,  87.5 ,  88.75,\n",
+       "        90.  ])</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'>0.0 1.875 3.75 ... 356.2 358.1</div><input id='attrs-bed5af3d-7ee4-44b2-a32a-4cabbb8db09e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bed5af3d-7ee4-44b2-a32a-4cabbb8db09e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69b892e3-1316-4bba-9a97-8620f3b72d53' class='xr-var-data-in' type='checkbox'><label for='data-69b892e3-1316-4bba-9a97-8620f3b72d53' 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.   ,   1.875,   3.75 ,   5.625,   7.5  ,   9.375,  11.25 ,  13.125,\n",
+       "        15.   ,  16.875,  18.75 ,  20.625,  22.5  ,  24.375,  26.25 ,  28.125,\n",
+       "        30.   ,  31.875,  33.75 ,  35.625,  37.5  ,  39.375,  41.25 ,  43.125,\n",
+       "        45.   ,  46.875,  48.75 ,  50.625,  52.5  ,  54.375,  56.25 ,  58.125,\n",
+       "        60.   ,  61.875,  63.75 ,  65.625,  67.5  ,  69.375,  71.25 ,  73.125,\n",
+       "        75.   ,  76.875,  78.75 ,  80.625,  82.5  ,  84.375,  86.25 ,  88.125,\n",
+       "        90.   ,  91.875,  93.75 ,  95.625,  97.5  ,  99.375, 101.25 , 103.125,\n",
+       "       105.   , 106.875, 108.75 , 110.625, 112.5  , 114.375, 116.25 , 118.125,\n",
+       "       120.   , 121.875, 123.75 , 125.625, 127.5  , 129.375, 131.25 , 133.125,\n",
+       "       135.   , 136.875, 138.75 , 140.625, 142.5  , 144.375, 146.25 , 148.125,\n",
+       "       150.   , 151.875, 153.75 , 155.625, 157.5  , 159.375, 161.25 , 163.125,\n",
+       "       165.   , 166.875, 168.75 , 170.625, 172.5  , 174.375, 176.25 , 178.125,\n",
+       "       180.   , 181.875, 183.75 , 185.625, 187.5  , 189.375, 191.25 , 193.125,\n",
+       "       195.   , 196.875, 198.75 , 200.625, 202.5  , 204.375, 206.25 , 208.125,\n",
+       "       210.   , 211.875, 213.75 , 215.625, 217.5  , 219.375, 221.25 , 223.125,\n",
+       "       225.   , 226.875, 228.75 , 230.625, 232.5  , 234.375, 236.25 , 238.125,\n",
+       "       240.   , 241.875, 243.75 , 245.625, 247.5  , 249.375, 251.25 , 253.125,\n",
+       "       255.   , 256.875, 258.75 , 260.625, 262.5  , 264.375, 266.25 , 268.125,\n",
+       "       270.   , 271.875, 273.75 , 275.625, 277.5  , 279.375, 281.25 , 283.125,\n",
+       "       285.   , 286.875, 288.75 , 290.625, 292.5  , 294.375, 296.25 , 298.125,\n",
+       "       300.   , 301.875, 303.75 , 305.625, 307.5  , 309.375, 311.25 , 313.125,\n",
+       "       315.   , 316.875, 318.75 , 320.625, 322.5  , 324.375, 326.25 , 328.125,\n",
+       "       330.   , 331.875, 333.75 , 335.625, 337.5  , 339.375, 341.25 , 343.125,\n",
+       "       345.   , 346.875, 348.75 , 350.625, 352.5  , 354.375, 356.25 , 358.125])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-211f6f62-8f7e-4427-8a1d-b2abb9d2d207' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-211f6f62-8f7e-4427-8a1d-b2abb9d2d207' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'ts' (lat: 145, lon: 192)>\n",
+       "array([[0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       ...,\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)\n",
+       "Coordinates:\n",
+       "  * lat      (lat) float64 -90.0 -88.75 -87.5 -86.25 ... 86.25 87.5 88.75 90.0\n",
+       "  * lon      (lon) float64 0.0 1.875 3.75 5.625 7.5 ... 352.5 354.4 356.2 358.1"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_day.ts[0] - ds.ts[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "878b6b6a-7651-47cf-9618-ae50dfc15e2c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x1649790a0>"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "(ds_gra_day.ts[-1]-ds.ts[-1]).plot()  # Just checking there ARE same"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "95c405c5-10d9-4017-b2f6-86567eb50d8c",
+   "metadata": {},
+   "source": [
+    "### 2.5 Hour"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "2be8eafa-dd75-4a78-89f7-6792f8a13352",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_gra_hour = ds.temporal.group_average(\"ts\", freq=\"hour\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "6418c31e-e638-4536-b45d-5d7f32642ba9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1872, 145, 192)"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_hour.ts.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "e47c850e-72f6-4eb0-8dd7-af5653ca4ffc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       ".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.DataArray &#x27;ts&#x27; (lat: 145, lon: 192)&gt;\n",
+       "array([[0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       ...,\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)\n",
+       "Coordinates:\n",
+       "  * lat      (lat) float64 -90.0 -88.75 -87.5 -86.25 ... 86.25 87.5 88.75 90.0\n",
+       "  * lon      (lon) float64 0.0 1.875 3.75 5.625 7.5 ... 352.5 354.4 356.2 358.1\n",
+       "    time     datetime64[ns] 1850-01-16T12:00:00</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'ts'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 145</li><li><span class='xr-has-index'>lon</span>: 192</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-4eb7639d-6e87-4c16-84dd-0802710a2744' class='xr-array-in' type='checkbox' checked><label for='section-4eb7639d-6e87-4c16-84dd-0802710a2744' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0</span></div><div class='xr-array-data'><pre>array([[0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       ...,\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-96e45d7c-00aa-4963-b90b-5cdf30489c1d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-96e45d7c-00aa-4963-b90b-5cdf30489c1d' 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'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.75 -87.5 ... 88.75 90.0</div><input id='attrs-beb43317-034b-4eff-b661-dfe224dacb27' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-beb43317-034b-4eff-b661-dfe224dacb27' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-76cc4ca3-1125-4d23-82b4-7ea74637c64a' class='xr-var-data-in' type='checkbox'><label for='data-76cc4ca3-1125-4d23-82b4-7ea74637c64a' 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([-90.  , -88.75, -87.5 , -86.25, -85.  , -83.75, -82.5 , -81.25, -80.  ,\n",
+       "       -78.75, -77.5 , -76.25, -75.  , -73.75, -72.5 , -71.25, -70.  , -68.75,\n",
+       "       -67.5 , -66.25, -65.  , -63.75, -62.5 , -61.25, -60.  , -58.75, -57.5 ,\n",
+       "       -56.25, -55.  , -53.75, -52.5 , -51.25, -50.  , -48.75, -47.5 , -46.25,\n",
+       "       -45.  , -43.75, -42.5 , -41.25, -40.  , -38.75, -37.5 , -36.25, -35.  ,\n",
+       "       -33.75, -32.5 , -31.25, -30.  , -28.75, -27.5 , -26.25, -25.  , -23.75,\n",
+       "       -22.5 , -21.25, -20.  , -18.75, -17.5 , -16.25, -15.  , -13.75, -12.5 ,\n",
+       "       -11.25, -10.  ,  -8.75,  -7.5 ,  -6.25,  -5.  ,  -3.75,  -2.5 ,  -1.25,\n",
+       "         0.  ,   1.25,   2.5 ,   3.75,   5.  ,   6.25,   7.5 ,   8.75,  10.  ,\n",
+       "        11.25,  12.5 ,  13.75,  15.  ,  16.25,  17.5 ,  18.75,  20.  ,  21.25,\n",
+       "        22.5 ,  23.75,  25.  ,  26.25,  27.5 ,  28.75,  30.  ,  31.25,  32.5 ,\n",
+       "        33.75,  35.  ,  36.25,  37.5 ,  38.75,  40.  ,  41.25,  42.5 ,  43.75,\n",
+       "        45.  ,  46.25,  47.5 ,  48.75,  50.  ,  51.25,  52.5 ,  53.75,  55.  ,\n",
+       "        56.25,  57.5 ,  58.75,  60.  ,  61.25,  62.5 ,  63.75,  65.  ,  66.25,\n",
+       "        67.5 ,  68.75,  70.  ,  71.25,  72.5 ,  73.75,  75.  ,  76.25,  77.5 ,\n",
+       "        78.75,  80.  ,  81.25,  82.5 ,  83.75,  85.  ,  86.25,  87.5 ,  88.75,\n",
+       "        90.  ])</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'>0.0 1.875 3.75 ... 356.2 358.1</div><input id='attrs-e16445c3-dc9a-4d63-a4a4-492dfa63cf9b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e16445c3-dc9a-4d63-a4a4-492dfa63cf9b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2405c4d-c64e-44b0-97b2-dc3a4a7dd451' class='xr-var-data-in' type='checkbox'><label for='data-a2405c4d-c64e-44b0-97b2-dc3a4a7dd451' 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.   ,   1.875,   3.75 ,   5.625,   7.5  ,   9.375,  11.25 ,  13.125,\n",
+       "        15.   ,  16.875,  18.75 ,  20.625,  22.5  ,  24.375,  26.25 ,  28.125,\n",
+       "        30.   ,  31.875,  33.75 ,  35.625,  37.5  ,  39.375,  41.25 ,  43.125,\n",
+       "        45.   ,  46.875,  48.75 ,  50.625,  52.5  ,  54.375,  56.25 ,  58.125,\n",
+       "        60.   ,  61.875,  63.75 ,  65.625,  67.5  ,  69.375,  71.25 ,  73.125,\n",
+       "        75.   ,  76.875,  78.75 ,  80.625,  82.5  ,  84.375,  86.25 ,  88.125,\n",
+       "        90.   ,  91.875,  93.75 ,  95.625,  97.5  ,  99.375, 101.25 , 103.125,\n",
+       "       105.   , 106.875, 108.75 , 110.625, 112.5  , 114.375, 116.25 , 118.125,\n",
+       "       120.   , 121.875, 123.75 , 125.625, 127.5  , 129.375, 131.25 , 133.125,\n",
+       "       135.   , 136.875, 138.75 , 140.625, 142.5  , 144.375, 146.25 , 148.125,\n",
+       "       150.   , 151.875, 153.75 , 155.625, 157.5  , 159.375, 161.25 , 163.125,\n",
+       "       165.   , 166.875, 168.75 , 170.625, 172.5  , 174.375, 176.25 , 178.125,\n",
+       "       180.   , 181.875, 183.75 , 185.625, 187.5  , 189.375, 191.25 , 193.125,\n",
+       "       195.   , 196.875, 198.75 , 200.625, 202.5  , 204.375, 206.25 , 208.125,\n",
+       "       210.   , 211.875, 213.75 , 215.625, 217.5  , 219.375, 221.25 , 223.125,\n",
+       "       225.   , 226.875, 228.75 , 230.625, 232.5  , 234.375, 236.25 , 238.125,\n",
+       "       240.   , 241.875, 243.75 , 245.625, 247.5  , 249.375, 251.25 , 253.125,\n",
+       "       255.   , 256.875, 258.75 , 260.625, 262.5  , 264.375, 266.25 , 268.125,\n",
+       "       270.   , 271.875, 273.75 , 275.625, 277.5  , 279.375, 281.25 , 283.125,\n",
+       "       285.   , 286.875, 288.75 , 290.625, 292.5  , 294.375, 296.25 , 298.125,\n",
+       "       300.   , 301.875, 303.75 , 305.625, 307.5  , 309.375, 311.25 , 313.125,\n",
+       "       315.   , 316.875, 318.75 , 320.625, 322.5  , 324.375, 326.25 , 328.125,\n",
+       "       330.   , 331.875, 333.75 , 335.625, 337.5  , 339.375, 341.25 , 343.125,\n",
+       "       345.   , 346.875, 348.75 , 350.625, 352.5  , 354.375, 356.25 , 358.125])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1850-01-16T12:00:00</div><input id='attrs-566ee881-1dd7-4f22-9cbe-a123ba3459f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-566ee881-1dd7-4f22-9cbe-a123ba3459f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-209e0a25-c4eb-498d-bd08-5e6e9cf41676' class='xr-var-data-in' type='checkbox'><label for='data-209e0a25-c4eb-498d-bd08-5e6e9cf41676' 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;1850-01-16T12:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d0977d9a-8a5e-4db6-b39d-742abfea6ba6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d0977d9a-8a5e-4db6-b39d-742abfea6ba6' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'ts' (lat: 145, lon: 192)>\n",
+       "array([[0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       ...,\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.],\n",
+       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)\n",
+       "Coordinates:\n",
+       "  * lat      (lat) float64 -90.0 -88.75 -87.5 -86.25 ... 86.25 87.5 88.75 90.0\n",
+       "  * lon      (lon) float64 0.0 1.875 3.75 5.625 7.5 ... 352.5 354.4 356.2 358.1\n",
+       "    time     datetime64[ns] 1850-01-16T12:00:00"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_gra_hour.ts[0] - ds.ts[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "c48c0ef6-3819-40fe-8cd0-d8df3b451827",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x1648cce50>"
+      ]
+     },
+     "execution_count": 38,
+     "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": [
+    "(ds_gra_hour.ts[-1]-ds.ts[-1]).plot()  # Just checking there ARE same"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "90837e4d-80b9-4829-81dc-cc58fb995df2",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "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
+}