diff --git a/docs/examples/climatology-and-departures.ipynb b/docs/examples/climatology-and-departures.ipynb
index d27e52d8..a78d381b 100644
--- a/docs/examples/climatology-and-departures.ipynb
+++ b/docs/examples/climatology-and-departures.ipynb
@@ -7,11 +7,9 @@
    "source": [
     "# Calculating Climatology and Departures from Time Series Data\n",
     "\n",
-    "Author: [Tom Vo](https://github.com/tomvothecoder/)\n",
+    "Author: [Tom Vo](https://github.com/tomvothecoder/) & [Jiwoo Lee](https://github.com/lee1043/)\n",
     "\n",
-    "Date: 05/27/22\n",
-    "\n",
-    "Last Updated: 2/27/23\n",
+    "Updated: 04/01/24 (v0.6.1)\n",
     "\n",
     "Related APIs:\n",
     "\n",
@@ -4486,7 +4484,7 @@
     "    freq=\"season\",\n",
     "    weighted=True,\n",
     "    season_config={\"dec_mode\": \"DJF\", \"drop_incomplete_djf\": True},\n",
-    ")\n"
+    ")"
    ]
   },
   {
diff --git a/docs/examples/temporal-average.ipynb b/docs/examples/temporal-average.ipynb
index 2453712c..49ecc157 100644
--- a/docs/examples/temporal-average.ipynb
+++ b/docs/examples/temporal-average.ipynb
@@ -6,11 +6,9 @@
    "source": [
     "# Calculate Time Averages from Time Series Data\n",
     "\n",
-    "Author: [Tom Vo](https://github.com/tomvothecoder/)\n",
+    "Author: [Tom Vo](https://github.com/tomvothecoder/) & [Jiwoo Lee](https://github.com/lee1043/)\n",
     "\n",
-    "Date: 05/27/22\n",
-    "\n",
-    "Last Edited: 08/17/22 (v0.3.1)\n",
+    "Updated: 04/01/24 [xcdat v0.6.1]\n",
     "\n",
     "Related APIs:\n",
     "\n",
@@ -367,6 +365,11 @@
        "  grid-column: 4;\n",
        "}\n",
        "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
        ".xr-var-name,\n",
        ".xr-var-dims,\n",
        ".xr-var-dtype,\n",
@@ -388,14 +391,16 @@
        "}\n",
        "\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-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",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
        "  display: block;\n",
        "}\n",
        "\n",
@@ -405,13 +410,16 @@
        "\n",
        ".xr-var-name span,\n",
        ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
        ".xr-attrs {\n",
        "  padding-left: 25px !important;\n",
        "}\n",
        "\n",
        ".xr-attrs,\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
        "  grid-column: 1 / -1;\n",
        "}\n",
        "\n",
@@ -449,7 +457,8 @@
        "}\n",
        "\n",
        ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
        "  display: inline-block;\n",
        "  vertical-align: middle;\n",
        "  width: 1em;\n",
@@ -458,19 +467,19 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 221MB\n",
        "Dimensions:    (time: 1980, bnds: 2, lat: 145, lon: 192)\n",
        "Coordinates:\n",
-       "  * time       (time) datetime64[ns] 1850-01-16T12:00:00 ... 2014-12-16T12:00:00\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 ... 352.5 354.4 356.2 358.1\n",
-       "    height     float64 2.0\n",
+       "  * lat        (lat) float64 1kB -90.0 -88.75 -87.5 -86.25 ... 87.5 88.75 90.0\n",
+       "  * lon        (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 354.4 356.2 358.1\n",
+       "    height     float64 8B 2.0\n",
+       "  * time       (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:00:00\n",
        "Dimensions without coordinates: bnds\n",
        "Data variables:\n",
-       "    time_bnds  (time, bnds) datetime64[ns] 1850-01-01 1850-02-01 ... 2015-01-01\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",
-       "    tas        (time, lat, lon) float32 -27.19 -27.19 -27.19 ... -25.29 -25.29\n",
+       "    time_bnds  (time, bnds) object 32kB ...\n",
+       "    lat_bnds   (lat, bnds) float64 2kB ...\n",
+       "    lon_bnds   (lon, bnds) float64 3kB ...\n",
+       "    tas        (time, lat, lon) float32 220MB -27.19 -27.19 ... -25.29 -25.29\n",
        "Attributes: (12/48)\n",
        "    Conventions:                     CF-1.7 CMIP-6.2\n",
        "    activity_id:                     CMIP\n",
@@ -484,10 +493,7 @@
        "    license:                         CMIP6 model data produced by CSIRO is li...\n",
        "    cmor_version:                    3.4.0\n",
        "    tracking_id:                     hdl:21.14100/af78ae5e-f3a6-4e99-8cfe-5f2...\n",
-       "    DODS_EXTRA.Unlimited_Dimension:  time</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-1741a959-3aa7-42ef-a59b-ff7476ce11f8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1741a959-3aa7-42ef-a59b-ff7476ce11f8' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1980</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 145</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-94fb9aca-c8bb-4ed7-9188-7578a9cb8fad' class='xr-section-summary-in' type='checkbox'  checked><label for='section-94fb9aca-c8bb-4ed7-9188-7578a9cb8fad' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1850-01-16T12:00:00 ... 2014-12-...</div><input id='attrs-e4e5565a-f553-42a0-b3c7-1c7759abde2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e4e5565a-f553-42a0-b3c7-1c7759abde2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e333183-0383-4dc8-b6ee-02e97f139aba' class='xr-var-data-in' type='checkbox'><label for='data-1e333183-0383-4dc8-b6ee-02e97f139aba' 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><dt><span>_ChunkSizes :</span></dt><dd>1</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;2014-10-16T12:00:00.000000000&#x27;,\n",
-       "       &#x27;2014-11-16T00:00:00.000000000&#x27;, &#x27;2014-12-16T12:00:00.000000000&#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-d451dcc2-dc74-4bb6-9727-091420b2da8d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d451dcc2-dc74-4bb6-9727-091420b2da8d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64163617-4abf-4071-becb-6c0aeb6f4b3d' class='xr-var-data-in' type='checkbox'><label for='data-64163617-4abf-4071-becb-6c0aeb6f4b3d' 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",
+       "    DODS_EXTRA.Unlimited_Dimension:  time</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-3c05f936-ca87-4abf-8d6b-d99c848f8967' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3c05f936-ca87-4abf-8d6b-d99c848f8967' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1980</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 145</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-0a5b41cc-c55f-46fe-8cb0-b79f75ce9143' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0a5b41cc-c55f-46fe-8cb0-b79f75ce9143' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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-7d3e51a8-b132-43da-a77a-683e8a0fc76a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d3e51a8-b132-43da-a77a-683e8a0fc76a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a5acf52-2d27-4192-a334-e8c910644106' class='xr-var-data-in' type='checkbox'><label for='data-5a5acf52-2d27-4192-a334-e8c910644106' 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",
@@ -503,7 +509,7 @@
        "        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-693b3219-6c73-49b7-b16b-0024971ef274' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-693b3219-6c73-49b7-b16b-0024971ef274' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62fa2bf3-66dd-4e39-8a5c-263c2d26064f' class='xr-var-data-in' type='checkbox'><label for='data-62fa2bf3-66dd-4e39-8a5c-263c2d26064f' 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",
+       "        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-4991656d-24e9-462b-8973-804ec84141a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4991656d-24e9-462b-8973-804ec84141a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5d51085-a5f5-4405-bdb9-b8e75fa22e97' class='xr-var-data-in' type='checkbox'><label for='data-a5d51085-a5f5-4405-bdb9-b8e75fa22e97' 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",
@@ -526,26 +532,14 @@
        "       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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-0797e814-6c7e-4f52-b6bc-837a96b8448a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0797e814-6c7e-4f52-b6bc-837a96b8448a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-12c23df6-d5c6-422d-881d-f83aeecc96a5' class='xr-var-data-in' type='checkbox'><label for='data-12c23df6-d5c6-422d-881d-f83aeecc96a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0ef64dc2-354f-4611-ae81-94f430cf0a8c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0ef64dc2-354f-4611-ae81-94f430cf0a8c' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a9c7b4a3-b154-4dd4-990b-621bbb307642' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a9c7b4a3-b154-4dd4-990b-621bbb307642' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-441007cc-a813-4bc9-8bdf-0a22bd9b3ddc' class='xr-var-data-in' type='checkbox'><label for='data-441007cc-a813-4bc9-8bdf-0a22bd9b3ddc' 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>_ChunkSizes :</span></dt><dd>[1 2]</dd></dl></div><div class='xr-var-data'><pre>array([[&#x27;1850-01-01T00:00:00.000000000&#x27;, &#x27;1850-02-01T00:00:00.000000000&#x27;],\n",
-       "       [&#x27;1850-02-01T00:00:00.000000000&#x27;, &#x27;1850-03-01T00:00:00.000000000&#x27;],\n",
-       "       [&#x27;1850-03-01T00:00:00.000000000&#x27;, &#x27;1850-04-01T00:00:00.000000000&#x27;],\n",
-       "       ...,\n",
-       "       [&#x27;2014-10-01T00:00:00.000000000&#x27;, &#x27;2014-11-01T00:00:00.000000000&#x27;],\n",
-       "       [&#x27;2014-11-01T00:00:00.000000000&#x27;, &#x27;2014-12-01T00:00:00.000000000&#x27;],\n",
-       "       [&#x27;2014-12-01T00:00:00.000000000&#x27;, &#x27;2015-01-01T00:00:00.000000000&#x27;]],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-62fbd620-ab46-44e9-8716-c0fd70208ba1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62fbd620-ab46-44e9-8716-c0fd70208ba1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56a6bd03-030d-44ed-b415-c0a1ccb4e931' class='xr-var-data-in' type='checkbox'><label for='data-56a6bd03-030d-44ed-b415-c0a1ccb4e931' 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>_ChunkSizes :</span></dt><dd>[145   2]</dd></dl></div><div class='xr-var-data'><pre>array([[-90.   , -89.375],\n",
-       "       [-89.375, -88.125],\n",
-       "       [-88.125, -86.875],\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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-93d69da6-96ff-4189-9c7c-3118092445f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-93d69da6-96ff-4189-9c7c-3118092445f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e71bd7a9-5251-4a56-9a97-729d9132941f' class='xr-var-data-in' type='checkbox'><label for='data-e71bd7a9-5251-4a56-9a97-729d9132941f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</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'>object</div><div class='xr-var-preview xr-preview'>1850-01-16 12:00:00 ... 2014-12-...</div><input id='attrs-c7e125f5-bb70-470d-8380-c9e670da6691' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c7e125f5-bb70-470d-8380-c9e670da6691' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-efb23d2d-7a90-48df-a84d-7dec10277103' class='xr-var-data-in' type='checkbox'><label for='data-efb23d2d-7a90-48df-a84d-7dec10277103' 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><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeProlepticGregorian(1850, 1, 16, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeProlepticGregorian(1850, 2, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeProlepticGregorian(1850, 3, 16, 12, 0, 0, 0, has_year_zero=True),\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-98099d1e-d8ea-4efb-a8e3-df9c0df8ec9f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98099d1e-d8ea-4efb-a8e3-df9c0df8ec9f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ccf85e6d-99be-4fb6-9432-29d089d412c0' class='xr-var-data-in' type='checkbox'><label for='data-ccf85e6d-99be-4fb6-9432-29d089d412c0' 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>_ChunkSizes :</span></dt><dd>[192   2]</dd></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>tas</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-27.19 -27.19 ... -25.29 -25.29</div><input id='attrs-5628a180-e214-40a4-8078-5ba4784e34f2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5628a180-e214-40a4-8078-5ba4784e34f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-05c0bd1d-15e9-4962-9aa7-d1b76636f9d8' class='xr-var-data-in' type='checkbox'><label for='data-05c0bd1d-15e9-4962-9aa7-d1b76636f9d8' 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([[[-27.186966 , -27.186966 , -27.186966 , ..., -27.186966 ,\n",
+       "       cftime.DatetimeProlepticGregorian(2014, 10, 16, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeProlepticGregorian(2014, 11, 16, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeProlepticGregorian(2014, 12, 16, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f33dde60-2d48-4538-91ec-6f24ae571a2c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f33dde60-2d48-4538-91ec-6f24ae571a2c' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c7fedac4-5df1-460a-af8f-3a3e9d5d05cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c7fedac4-5df1-460a-af8f-3a3e9d5d05cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eeea8a8d-0e99-4c8c-b50d-57047e0361d0' class='xr-var-data-in' type='checkbox'><label for='data-eeea8a8d-0e99-4c8c-b50d-57047e0361d0' 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>_ChunkSizes :</span></dt><dd>[1 2]</dd></dl></div><div class='xr-var-data'><pre>[3960 values with dtype=object]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3baf878a-d103-4392-8ced-ad703a7ef53b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3baf878a-d103-4392-8ced-ad703a7ef53b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67eab732-58f5-43b4-817d-0c4e95efd081' class='xr-var-data-in' type='checkbox'><label for='data-67eab732-58f5-43b4-817d-0c4e95efd081' 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>_ChunkSizes :</span></dt><dd>[145   2]</dd></dl></div><div class='xr-var-data'><pre>[290 values with dtype=float64]</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-1536fe8f-207c-4634-8893-ae49891e9e89' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1536fe8f-207c-4634-8893-ae49891e9e89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48a99f94-2abf-491a-82de-c1953eccd6d3' class='xr-var-data-in' type='checkbox'><label for='data-48a99f94-2abf-491a-82de-c1953eccd6d3' 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>_ChunkSizes :</span></dt><dd>[192   2]</dd></dl></div><div class='xr-var-data'><pre>[384 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-27.19 -27.19 ... -25.29 -25.29</div><input id='attrs-fb49267e-84d0-4455-bd96-1217188086a9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fb49267e-84d0-4455-bd96-1217188086a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8873175-3ca4-437c-9aa5-625f33be242b' class='xr-var-data-in' type='checkbox'><label for='data-a8873175-3ca4-437c-9aa5-625f33be242b' 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([[[-27.186966 , -27.186966 , -27.186966 , ..., -27.186966 ,\n",
        "         -27.186966 , -27.186966 ],\n",
        "        [-25.952972 , -25.990189 , -26.04216  , ..., -25.809921 ,\n",
        "         -25.856598 , -25.905975 ],\n",
@@ -585,7 +579,29 @@
        "        [-24.629013 , -24.613388 , -24.549866 , ..., -24.752045 ,\n",
        "         -24.721603 , -24.666412 ],\n",
        "        [-25.28923  , -25.28923  , -25.28923  , ..., -25.28923  ,\n",
-       "         -25.28923  , -25.28923  ]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-539b5ec2-3cd6-439b-97d0-0da68a0657c7' class='xr-section-summary-in' type='checkbox'  ><label for='section-539b5ec2-3cd6-439b-97d0-0da68a0657c7' class='xr-section-summary' >Attributes: <span>(48)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>0.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>87658.0</dd><dt><span>creation_date :</span></dt><dd>2020-06-05T04:06:11Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.30</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.CSIRO.ACCESS-ESM1-5.historical.none.r10i1p1f1</dd><dt><span>grid :</span></dt><dd>native atmosphere N96 grid (145x192 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>history :</span></dt><dd>2020-06-05T04:06:11Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 CMIP-6.2 and CF standards.</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia</dd><dt><span>institution_id :</span></dt><dd>CSIRO</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>nominal_resolution :</span></dt><dd>250 km</dd><dt><span>notes :</span></dt><dd>Exp: ESM-historical; Local ID: HI-14; Variable: tas ([&#x27;fld_s03i236&#x27;])</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>ACCESS-ESM1-5</dd><dt><span>parent_time_units :</span></dt><dd>days since 0101-1-1</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>10</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>run_variant :</span></dt><dd>forcing: GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4, CFC11, CFC12, CFC113, HCFC22, HFC125, HFC134a)</dd><dt><span>source :</span></dt><dd>ACCESS-ESM1.5 (2019): \n",
+       "         -25.28923  , -25.28923  ]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8b0d331c-7002-471d-b485-4708fcf2acbf' class='xr-section-summary-in' type='checkbox'  ><label for='section-8b0d331c-7002-471d-b485-4708fcf2acbf' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-77bdb3b8-8860-43d8-91bf-ae0eca79a37d' class='xr-index-data-in' type='checkbox'/><label for='index-77bdb3b8-8860-43d8-91bf-ae0eca79a37d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -90.0, -88.75,  -87.5, -86.25,  -85.0, -83.75,  -82.5, -81.25,  -80.0,\n",
+       "       -78.75,\n",
+       "       ...\n",
+       "        78.75,   80.0,  81.25,   82.5,  83.75,   85.0,  86.25,   87.5,  88.75,\n",
+       "         90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=145))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-87435ba7-b699-4630-8a76-83b72b15458f' class='xr-index-data-in' type='checkbox'/><label for='index-87435ba7-b699-4630-8a76-83b72b15458f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([    0.0,   1.875,    3.75,   5.625,     7.5,   9.375,   11.25,  13.125,\n",
+       "          15.0,  16.875,\n",
+       "       ...\n",
+       "        341.25, 343.125,   345.0, 346.875,  348.75, 350.625,   352.5, 354.375,\n",
+       "        356.25, 358.125],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-891ef422-eb80-4724-9996-02870fbd2df6' class='xr-index-data-in' type='checkbox'/><label for='index-891ef422-eb80-4724-9996-02870fbd2df6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-16 12:00:00, 1850-02-15 00:00:00, 1850-03-16 12:00:00,\n",
+       "             1850-04-16 00:00:00, 1850-05-16 12:00:00, 1850-06-16 00:00:00,\n",
+       "             1850-07-16 12:00:00, 1850-08-16 12:00:00, 1850-09-16 00:00:00,\n",
+       "             1850-10-16 12:00:00,\n",
+       "             ...\n",
+       "             2014-03-16 12:00:00, 2014-04-16 00:00:00, 2014-05-16 12:00:00,\n",
+       "             2014-06-16 00:00:00, 2014-07-16 12:00:00, 2014-08-16 12:00:00,\n",
+       "             2014-09-16 00:00:00, 2014-10-16 12:00:00, 2014-11-16 00:00:00,\n",
+       "             2014-12-16 12:00:00],\n",
+       "            dtype=&#x27;object&#x27;,\n",
+       "            length=1980,\n",
+       "            calendar=&#x27;proleptic_gregorian&#x27;,\n",
+       "            freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-db6bbef0-5211-4db6-8fb4-0dea51e8c338' class='xr-section-summary-in' type='checkbox'  ><label for='section-db6bbef0-5211-4db6-8fb4-0dea51e8c338' class='xr-section-summary' >Attributes: <span>(48)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>0.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>87658.0</dd><dt><span>creation_date :</span></dt><dd>2020-06-05T04:06:11Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.30</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.CSIRO.ACCESS-ESM1-5.historical.none.r10i1p1f1</dd><dt><span>grid :</span></dt><dd>native atmosphere N96 grid (145x192 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>history :</span></dt><dd>2020-06-05T04:06:11Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 CMIP-6.2 and CF standards.</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia</dd><dt><span>institution_id :</span></dt><dd>CSIRO</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>nominal_resolution :</span></dt><dd>250 km</dd><dt><span>notes :</span></dt><dd>Exp: ESM-historical; Local ID: HI-14; Variable: tas ([&#x27;fld_s03i236&#x27;])</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>ACCESS-ESM1-5</dd><dt><span>parent_time_units :</span></dt><dd>days since 0101-1-1</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>10</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>run_variant :</span></dt><dd>forcing: GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4, CFC11, CFC12, CFC113, HCFC22, HFC125, HFC134a)</dd><dt><span>source :</span></dt><dd>ACCESS-ESM1.5 (2019): \n",
        "aerosol: CLASSIC (v1.0)\n",
        "atmos: HadGAM2 (r1.1, N96; 192 x 145 longitude/latitude; 38 levels; top level 39255 m)\n",
        "atmosChem: none\n",
@@ -596,19 +612,19 @@
        "seaIce: CICE4.1 (same grid as ocean)</dd><dt><span>source_id :</span></dt><dd>ACCESS-ESM1-5</dd><dt><span>source_type :</span></dt><dd>AOGCM</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>Amon</dd><dt><span>table_info :</span></dt><dd>Creation Date:(30 April 2019) MD5:5bd755e94c2173cb3050a0f3480f60c4</dd><dt><span>title :</span></dt><dd>ACCESS-ESM1-5 output prepared for CMIP6</dd><dt><span>variable_id :</span></dt><dd>tas</dd><dt><span>variant_label :</span></dt><dd>r10i1p1f1</dd><dt><span>version :</span></dt><dd>v20200605</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by CSIRO is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment.  Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file). The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.4.0</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/af78ae5e-f3a6-4e99-8cfe-5f29eb467cd1</dd><dt><span>DODS_EXTRA.Unlimited_Dimension :</span></dt><dd>time</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
-       "<xarray.Dataset>\n",
+       "<xarray.Dataset> Size: 221MB\n",
        "Dimensions:    (time: 1980, bnds: 2, lat: 145, lon: 192)\n",
        "Coordinates:\n",
-       "  * time       (time) datetime64[ns] 1850-01-16T12:00:00 ... 2014-12-16T12:00:00\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 ... 352.5 354.4 356.2 358.1\n",
-       "    height     float64 2.0\n",
+       "  * lat        (lat) float64 1kB -90.0 -88.75 -87.5 -86.25 ... 87.5 88.75 90.0\n",
+       "  * lon        (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 354.4 356.2 358.1\n",
+       "    height     float64 8B 2.0\n",
+       "  * time       (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:00:00\n",
        "Dimensions without coordinates: bnds\n",
        "Data variables:\n",
-       "    time_bnds  (time, bnds) datetime64[ns] ...\n",
-       "    lat_bnds   (lat, bnds) float64 ...\n",
-       "    lon_bnds   (lon, bnds) float64 ...\n",
-       "    tas        (time, lat, lon) float32 -27.19 -27.19 -27.19 ... -25.29 -25.29\n",
+       "    time_bnds  (time, bnds) object 32kB ...\n",
+       "    lat_bnds   (lat, bnds) float64 2kB ...\n",
+       "    lon_bnds   (lon, bnds) float64 3kB ...\n",
+       "    tas        (time, lat, lon) float32 220MB -27.19 -27.19 ... -25.29 -25.29\n",
        "Attributes: (12/48)\n",
        "    Conventions:                     CF-1.7 CMIP-6.2\n",
        "    activity_id:                     CMIP\n",
@@ -918,6 +934,11 @@
        "  grid-column: 4;\n",
        "}\n",
        "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
        ".xr-var-name,\n",
        ".xr-var-dims,\n",
        ".xr-var-dtype,\n",
@@ -939,14 +960,16 @@
        "}\n",
        "\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-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",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
        "  display: block;\n",
        "}\n",
        "\n",
@@ -956,13 +979,16 @@
        "\n",
        ".xr-var-name span,\n",
        ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
        ".xr-attrs {\n",
        "  padding-left: 25px !important;\n",
        "}\n",
        "\n",
        ".xr-attrs,\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
        "  grid-column: 1 / -1;\n",
        "}\n",
        "\n",
@@ -1000,7 +1026,8 @@
        "}\n",
        "\n",
        ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
        "  display: inline-block;\n",
        "  vertical-align: middle;\n",
        "  width: 1em;\n",
@@ -1009,7 +1036,7 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tas&#x27; (lat: 145, lon: 192)&gt;\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tas&#x27; (lat: 145, lon: 192)&gt; Size: 223kB\n",
        "array([[-48.01481628, -48.01481628, -48.01481628, ..., -48.01481628,\n",
        "        -48.01481628, -48.01481628],\n",
        "       [-44.94085363, -44.97948214, -45.01815398, ..., -44.82408252,\n",
@@ -1024,14 +1051,14 @@
        "       [-19.07366375, -19.07366375, -19.07366375, ..., -19.07366375,\n",
        "        -19.07366375, -19.07366375]])\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",
-       "    height   float64 2.0\n",
+       "  * lat      (lat) float64 1kB -90.0 -88.75 -87.5 -86.25 ... 87.5 88.75 90.0\n",
+       "  * lon      (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 352.5 354.4 356.2 358.1\n",
+       "    height   float64 8B 2.0\n",
        "Attributes:\n",
        "    operation:  temporal_avg\n",
        "    mode:       average\n",
        "    freq:       month\n",
-       "    weighted:   True</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'tas'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>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-b3b0d5b1-680d-4568-977b-c94dd7f53588' class='xr-array-in' type='checkbox' checked><label for='section-b3b0d5b1-680d-4568-977b-c94dd7f53588' 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>-48.01 -48.01 -48.01 -48.01 -48.01 ... -19.07 -19.07 -19.07 -19.07</span></div><div class='xr-array-data'><pre>array([[-48.01481628, -48.01481628, -48.01481628, ..., -48.01481628,\n",
+       "    weighted:   True</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'tas'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>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-3e5ffbba-4920-40ce-b0ae-9470cb14f557' class='xr-array-in' type='checkbox' checked><label for='section-3e5ffbba-4920-40ce-b0ae-9470cb14f557' 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>-48.01 -48.01 -48.01 -48.01 -48.01 ... -19.07 -19.07 -19.07 -19.07</span></div><div class='xr-array-data'><pre>array([[-48.01481628, -48.01481628, -48.01481628, ..., -48.01481628,\n",
        "        -48.01481628, -48.01481628],\n",
        "       [-44.94085363, -44.97948214, -45.01815398, ..., -44.82408252,\n",
        "        -44.86273067, -44.9009281 ],\n",
@@ -1043,7 +1070,7 @@
        "       [-18.50778243, -18.49301854, -18.47902819, ..., -18.55410851,\n",
        "        -18.5406963 , -18.52413098],\n",
        "       [-19.07366375, -19.07366375, -19.07366375, ..., -19.07366375,\n",
-       "        -19.07366375, -19.07366375]])</pre></div></div></li><li class='xr-section-item'><input id='section-31bb316b-3d6e-48fe-90d8-17f01c1bb0eb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-31bb316b-3d6e-48fe-90d8-17f01c1bb0eb' 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-a1b11c47-166c-4201-a638-423f4e5c3e90' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a1b11c47-166c-4201-a638-423f4e5c3e90' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9546c1ed-6bbe-4134-9f92-89be9b537012' class='xr-var-data-in' type='checkbox'><label for='data-9546c1ed-6bbe-4134-9f92-89be9b537012' 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",
+       "        -19.07366375, -19.07366375]])</pre></div></div></li><li class='xr-section-item'><input id='section-c70c3ab1-f9d1-4e47-8c10-0f1c08a20e7f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c70c3ab1-f9d1-4e47-8c10-0f1c08a20e7f' 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-352b7338-fb3e-42e3-a12f-36b6b949165d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-352b7338-fb3e-42e3-a12f-36b6b949165d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1361be04-0953-446b-b62b-a08b8e18744b' class='xr-var-data-in' type='checkbox'><label for='data-1361be04-0953-446b-b62b-a08b8e18744b' 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",
@@ -1059,7 +1086,7 @@
        "        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-528df85e-d959-4178-831b-58950de43920' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-528df85e-d959-4178-831b-58950de43920' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-487e4d2b-f1f9-4985-ab80-326d52997881' class='xr-var-data-in' type='checkbox'><label for='data-487e4d2b-f1f9-4985-ab80-326d52997881' 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",
+       "        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-f0733fd6-5aa5-4b68-a3ae-7e345b89f3b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f0733fd6-5aa5-4b68-a3ae-7e345b89f3b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b08471e9-4344-4a94-ba31-6b0f12f07931' class='xr-var-data-in' type='checkbox'><label for='data-b08471e9-4344-4a94-ba31-6b0f12f07931' 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",
@@ -1082,10 +1109,20 @@
        "       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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-23e46b90-f12c-42cb-b776-98d8804e8378' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-23e46b90-f12c-42cb-b776-98d8804e8378' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99399c8f-5e95-44cc-a42f-8c911ddbef1b' class='xr-var-data-in' type='checkbox'><label for='data-99399c8f-5e95-44cc-a42f-8c911ddbef1b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f3e6a96c-6688-4650-bf29-7c8edb48e60a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f3e6a96c-6688-4650-bf29-7c8edb48e60a' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><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></dl></div></li></ul></div></div>"
+       "       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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-62808eca-14bc-4115-9159-ce1fc3ed2b1e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62808eca-14bc-4115-9159-ce1fc3ed2b1e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eee82a8a-c544-468e-a6f2-906854e2326a' class='xr-var-data-in' type='checkbox'><label for='data-eee82a8a-c544-468e-a6f2-906854e2326a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-72391c93-a1c7-4d5a-9a27-f4c52ecdf617' class='xr-section-summary-in' type='checkbox'  ><label for='section-72391c93-a1c7-4d5a-9a27-f4c52ecdf617' class='xr-section-summary' >Indexes: <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-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-baa316fb-9a54-4655-9c4d-d4a98765b22d' class='xr-index-data-in' type='checkbox'/><label for='index-baa316fb-9a54-4655-9c4d-d4a98765b22d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -90.0, -88.75,  -87.5, -86.25,  -85.0, -83.75,  -82.5, -81.25,  -80.0,\n",
+       "       -78.75,\n",
+       "       ...\n",
+       "        78.75,   80.0,  81.25,   82.5,  83.75,   85.0,  86.25,   87.5,  88.75,\n",
+       "         90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=145))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-76dbbc5b-1871-43fb-82ec-941c4588ddc0' class='xr-index-data-in' type='checkbox'/><label for='index-76dbbc5b-1871-43fb-82ec-941c4588ddc0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([    0.0,   1.875,    3.75,   5.625,     7.5,   9.375,   11.25,  13.125,\n",
+       "          15.0,  16.875,\n",
+       "       ...\n",
+       "        341.25, 343.125,   345.0, 346.875,  348.75, 350.625,   352.5, 354.375,\n",
+       "        356.25, 358.125],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=192))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cbb04b44-cf90-4bc0-9644-84f34a7ab327' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cbb04b44-cf90-4bc0-9644-84f34a7ab327' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><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></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
-       "<xarray.DataArray 'tas' (lat: 145, lon: 192)>\n",
+       "<xarray.DataArray 'tas' (lat: 145, lon: 192)> Size: 223kB\n",
        "array([[-48.01481628, -48.01481628, -48.01481628, ..., -48.01481628,\n",
        "        -48.01481628, -48.01481628],\n",
        "       [-44.94085363, -44.97948214, -45.01815398, ..., -44.82408252,\n",
@@ -1100,9 +1137,9 @@
        "       [-19.07366375, -19.07366375, -19.07366375, ..., -19.07366375,\n",
        "        -19.07366375, -19.07366375]])\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",
-       "    height   float64 2.0\n",
+       "  * lat      (lat) float64 1kB -90.0 -88.75 -87.5 -86.25 ... 87.5 88.75 90.0\n",
+       "  * lon      (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 352.5 354.4 356.2 358.1\n",
+       "    height   float64 8B 2.0\n",
        "Attributes:\n",
        "    operation:  temporal_avg\n",
        "    mode:       average\n",
@@ -1127,7 +1164,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x7f120aa2a9a0>"
+       "<matplotlib.collections.QuadMesh at 0x157ef6990>"
       ]
      },
      "execution_count": 5,
@@ -1136,14 +1173,12 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 432x288 with 2 Axes>"
+       "<Figure size 640x480 with 2 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -1462,6 +1497,11 @@
        "  grid-column: 4;\n",
        "}\n",
        "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
        ".xr-var-name,\n",
        ".xr-var-dims,\n",
        ".xr-var-dtype,\n",
@@ -1483,14 +1523,16 @@
        "}\n",
        "\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-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",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
        "  display: block;\n",
        "}\n",
        "\n",
@@ -1500,13 +1542,16 @@
        "\n",
        ".xr-var-name span,\n",
        ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
        ".xr-attrs {\n",
        "  padding-left: 25px !important;\n",
        "}\n",
        "\n",
        ".xr-attrs,\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
        "  grid-column: 1 / -1;\n",
        "}\n",
        "\n",
@@ -1544,7 +1589,8 @@
        "}\n",
        "\n",
        ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
        "  display: inline-block;\n",
        "  vertical-align: middle;\n",
        "  width: 1em;\n",
@@ -1553,19 +1599,19 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 221MB\n",
        "Dimensions:    (time: 1980, bnds: 2, lat: 145, lon: 192)\n",
        "Coordinates:\n",
-       "  * time       (time) datetime64[ns] 1850-01-16T12:00:00 ... 2014-12-16T12:00:00\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 ... 352.5 354.4 356.2 358.1\n",
-       "    height     float64 2.0\n",
+       "  * lat        (lat) float64 1kB -90.0 -88.75 -87.5 -86.25 ... 87.5 88.75 90.0\n",
+       "  * lon        (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 354.4 356.2 358.1\n",
+       "    height     float64 8B 2.0\n",
+       "  * time       (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:00:00\n",
        "Dimensions without coordinates: bnds\n",
        "Data variables:\n",
-       "    time_bnds  (time, bnds) datetime64[ns] 1850-01-01 1850-02-01 ... 2015-01-01\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",
-       "    tas        (time, lat, lon) float32 -27.19 -27.19 -27.19 ... -25.29 -25.29\n",
+       "    time_bnds  (time, bnds) object 32kB ...\n",
+       "    lat_bnds   (lat, bnds) float64 2kB ...\n",
+       "    lon_bnds   (lon, bnds) float64 3kB ...\n",
+       "    tas        (time, lat, lon) float32 220MB -27.19 -27.19 ... -25.29 -25.29\n",
        "Attributes: (12/48)\n",
        "    Conventions:                     CF-1.7 CMIP-6.2\n",
        "    activity_id:                     CMIP\n",
@@ -1579,10 +1625,7 @@
        "    license:                         CMIP6 model data produced by CSIRO is li...\n",
        "    cmor_version:                    3.4.0\n",
        "    tracking_id:                     hdl:21.14100/af78ae5e-f3a6-4e99-8cfe-5f2...\n",
-       "    DODS_EXTRA.Unlimited_Dimension:  time</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-03e17bde-08e8-4979-a7ef-413da9fb3a34' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-03e17bde-08e8-4979-a7ef-413da9fb3a34' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1980</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 145</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-9f3030ac-5c60-4b96-a68d-cd8cb2a7cc52' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9f3030ac-5c60-4b96-a68d-cd8cb2a7cc52' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1850-01-16T12:00:00 ... 2014-12-...</div><input id='attrs-4e71fd98-4c86-4ea3-b5b6-c715f72c49ca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e71fd98-4c86-4ea3-b5b6-c715f72c49ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-661cd064-2e06-4546-8122-4da730056c61' class='xr-var-data-in' type='checkbox'><label for='data-661cd064-2e06-4546-8122-4da730056c61' 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><dt><span>_ChunkSizes :</span></dt><dd>1</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;2014-10-16T12:00:00.000000000&#x27;,\n",
-       "       &#x27;2014-11-16T00:00:00.000000000&#x27;, &#x27;2014-12-16T12:00:00.000000000&#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-d4fef9dd-4f88-4584-b2a5-044d7b556f18' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d4fef9dd-4f88-4584-b2a5-044d7b556f18' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04927f41-29ba-45a1-a8af-65829c6ab7de' class='xr-var-data-in' type='checkbox'><label for='data-04927f41-29ba-45a1-a8af-65829c6ab7de' 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",
+       "    DODS_EXTRA.Unlimited_Dimension:  time</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-b0623419-1362-4ae6-b7f7-2b5bb9168c98' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b0623419-1362-4ae6-b7f7-2b5bb9168c98' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1980</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 145</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-9127b4ce-85be-42e5-b59b-0e71e2227cec' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9127b4ce-85be-42e5-b59b-0e71e2227cec' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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-aac4708c-39d3-4faf-a943-c4b6a878a5c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aac4708c-39d3-4faf-a943-c4b6a878a5c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3cebb249-cb76-498c-bdd6-7e55a00ec665' class='xr-var-data-in' type='checkbox'><label for='data-3cebb249-cb76-498c-bdd6-7e55a00ec665' 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",
@@ -1598,7 +1641,7 @@
        "        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-44eb6931-d5b5-4409-be0e-0aef54181575' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-44eb6931-d5b5-4409-be0e-0aef54181575' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e47a4ce4-185a-4abe-a59c-b90cc725deab' class='xr-var-data-in' type='checkbox'><label for='data-e47a4ce4-185a-4abe-a59c-b90cc725deab' 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",
+       "        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-9de057d5-c3d2-4d4b-9093-a294fc7fb1ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9de057d5-c3d2-4d4b-9093-a294fc7fb1ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5faa323b-ea95-4f98-88cc-a0a12ef2e9a3' class='xr-var-data-in' type='checkbox'><label for='data-5faa323b-ea95-4f98-88cc-a0a12ef2e9a3' 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",
@@ -1621,26 +1664,14 @@
        "       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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-664e39e1-8837-4bb6-b413-bd06a79342b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-664e39e1-8837-4bb6-b413-bd06a79342b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-540ae2db-b24d-4420-b040-48f80f6ddde4' class='xr-var-data-in' type='checkbox'><label for='data-540ae2db-b24d-4420-b040-48f80f6ddde4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e1f71cb4-5aef-4141-ba6d-65f8400df1c6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e1f71cb4-5aef-4141-ba6d-65f8400df1c6' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b1525c23-8292-4cb7-adaf-f713aa79aeec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b1525c23-8292-4cb7-adaf-f713aa79aeec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-849a30e4-a456-4fcc-98b4-9f30d9f9af31' class='xr-var-data-in' type='checkbox'><label for='data-849a30e4-a456-4fcc-98b4-9f30d9f9af31' 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>_ChunkSizes :</span></dt><dd>[1 2]</dd></dl></div><div class='xr-var-data'><pre>array([[&#x27;1850-01-01T00:00:00.000000000&#x27;, &#x27;1850-02-01T00:00:00.000000000&#x27;],\n",
-       "       [&#x27;1850-02-01T00:00:00.000000000&#x27;, &#x27;1850-03-01T00:00:00.000000000&#x27;],\n",
-       "       [&#x27;1850-03-01T00:00:00.000000000&#x27;, &#x27;1850-04-01T00:00:00.000000000&#x27;],\n",
-       "       ...,\n",
-       "       [&#x27;2014-10-01T00:00:00.000000000&#x27;, &#x27;2014-11-01T00:00:00.000000000&#x27;],\n",
-       "       [&#x27;2014-11-01T00:00:00.000000000&#x27;, &#x27;2014-12-01T00:00:00.000000000&#x27;],\n",
-       "       [&#x27;2014-12-01T00:00:00.000000000&#x27;, &#x27;2015-01-01T00:00:00.000000000&#x27;]],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f7729609-b9e5-42ca-8e7a-ff1a18a4b90a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7729609-b9e5-42ca-8e7a-ff1a18a4b90a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9def0ef4-1d62-4522-ba2b-a309023ed7a8' class='xr-var-data-in' type='checkbox'><label for='data-9def0ef4-1d62-4522-ba2b-a309023ed7a8' 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>_ChunkSizes :</span></dt><dd>[145   2]</dd></dl></div><div class='xr-var-data'><pre>array([[-90.   , -89.375],\n",
-       "       [-89.375, -88.125],\n",
-       "       [-88.125, -86.875],\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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-c5c790ff-1e4d-4c7c-95af-5b2c48482e9a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c5c790ff-1e4d-4c7c-95af-5b2c48482e9a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-758562b2-df4b-4b88-9f45-bad93720712b' class='xr-var-data-in' type='checkbox'><label for='data-758562b2-df4b-4b88-9f45-bad93720712b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</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'>object</div><div class='xr-var-preview xr-preview'>1850-01-16 12:00:00 ... 2014-12-...</div><input id='attrs-e3c56119-1402-4546-9ab1-415e3603e5a8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e3c56119-1402-4546-9ab1-415e3603e5a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-201b13c8-a539-436a-984d-f8e18725467a' class='xr-var-data-in' type='checkbox'><label for='data-201b13c8-a539-436a-984d-f8e18725467a' 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><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeProlepticGregorian(1850, 1, 16, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeProlepticGregorian(1850, 2, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeProlepticGregorian(1850, 3, 16, 12, 0, 0, 0, has_year_zero=True),\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-8c6b9fdf-1888-463b-af87-61e98a1edaf7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c6b9fdf-1888-463b-af87-61e98a1edaf7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-505af48a-c0c2-4ced-80d5-26654a6efeac' class='xr-var-data-in' type='checkbox'><label for='data-505af48a-c0c2-4ced-80d5-26654a6efeac' 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>_ChunkSizes :</span></dt><dd>[192   2]</dd></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>tas</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-27.19 -27.19 ... -25.29 -25.29</div><input id='attrs-d217702e-bb52-4c19-bb77-bde1cc553b1d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d217702e-bb52-4c19-bb77-bde1cc553b1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb5059ba-9cc4-4e09-b0c4-e4952fb6153d' class='xr-var-data-in' type='checkbox'><label for='data-cb5059ba-9cc4-4e09-b0c4-e4952fb6153d' 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([[[-27.186966 , -27.186966 , -27.186966 , ..., -27.186966 ,\n",
+       "       cftime.DatetimeProlepticGregorian(2014, 10, 16, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeProlepticGregorian(2014, 11, 16, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeProlepticGregorian(2014, 12, 16, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-477d4cfe-c0ef-455d-8d7b-6557190f6512' class='xr-section-summary-in' type='checkbox'  checked><label for='section-477d4cfe-c0ef-455d-8d7b-6557190f6512' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-42a90b43-1dd8-4ecc-a2e9-ffb6b1e28de8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42a90b43-1dd8-4ecc-a2e9-ffb6b1e28de8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d5dcba7-1626-44a0-8000-e62ffdaa3514' class='xr-var-data-in' type='checkbox'><label for='data-6d5dcba7-1626-44a0-8000-e62ffdaa3514' 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>_ChunkSizes :</span></dt><dd>[1 2]</dd></dl></div><div class='xr-var-data'><pre>[3960 values with dtype=object]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ad1d2ca4-952f-46d8-87e2-f3e168f34dda' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad1d2ca4-952f-46d8-87e2-f3e168f34dda' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8e47316-8728-458b-a389-efcb47e394a1' class='xr-var-data-in' type='checkbox'><label for='data-a8e47316-8728-458b-a389-efcb47e394a1' 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>_ChunkSizes :</span></dt><dd>[145   2]</dd></dl></div><div class='xr-var-data'><pre>[290 values with dtype=float64]</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-c34ac53c-49e8-4cc1-9b6e-709a0430a378' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c34ac53c-49e8-4cc1-9b6e-709a0430a378' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cdf6aa46-f373-42b5-8ce5-e2addf6ee64d' class='xr-var-data-in' type='checkbox'><label for='data-cdf6aa46-f373-42b5-8ce5-e2addf6ee64d' 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>_ChunkSizes :</span></dt><dd>[192   2]</dd></dl></div><div class='xr-var-data'><pre>[384 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-27.19 -27.19 ... -25.29 -25.29</div><input id='attrs-43ab34cc-ebed-48b1-a9ec-1786a8e4884c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-43ab34cc-ebed-48b1-a9ec-1786a8e4884c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97bb0abb-f836-4568-b2d1-f8664cb3e595' class='xr-var-data-in' type='checkbox'><label for='data-97bb0abb-f836-4568-b2d1-f8664cb3e595' 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([[[-27.186966 , -27.186966 , -27.186966 , ..., -27.186966 ,\n",
        "         -27.186966 , -27.186966 ],\n",
        "        [-25.952972 , -25.990189 , -26.04216  , ..., -25.809921 ,\n",
        "         -25.856598 , -25.905975 ],\n",
@@ -1680,7 +1711,29 @@
        "        [-24.629013 , -24.613388 , -24.549866 , ..., -24.752045 ,\n",
        "         -24.721603 , -24.666412 ],\n",
        "        [-25.28923  , -25.28923  , -25.28923  , ..., -25.28923  ,\n",
-       "         -25.28923  , -25.28923  ]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f50b5981-8147-4d60-95bb-15646dcb3943' class='xr-section-summary-in' type='checkbox'  ><label for='section-f50b5981-8147-4d60-95bb-15646dcb3943' class='xr-section-summary' >Attributes: <span>(48)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>0.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>87658.0</dd><dt><span>creation_date :</span></dt><dd>2020-06-05T04:06:11Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.30</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.CSIRO.ACCESS-ESM1-5.historical.none.r10i1p1f1</dd><dt><span>grid :</span></dt><dd>native atmosphere N96 grid (145x192 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>history :</span></dt><dd>2020-06-05T04:06:11Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 CMIP-6.2 and CF standards.</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia</dd><dt><span>institution_id :</span></dt><dd>CSIRO</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>nominal_resolution :</span></dt><dd>250 km</dd><dt><span>notes :</span></dt><dd>Exp: ESM-historical; Local ID: HI-14; Variable: tas ([&#x27;fld_s03i236&#x27;])</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>ACCESS-ESM1-5</dd><dt><span>parent_time_units :</span></dt><dd>days since 0101-1-1</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>10</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>run_variant :</span></dt><dd>forcing: GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4, CFC11, CFC12, CFC113, HCFC22, HFC125, HFC134a)</dd><dt><span>source :</span></dt><dd>ACCESS-ESM1.5 (2019): \n",
+       "         -25.28923  , -25.28923  ]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fe9089e6-8ce4-4307-9e01-e54f9f3678df' class='xr-section-summary-in' type='checkbox'  ><label for='section-fe9089e6-8ce4-4307-9e01-e54f9f3678df' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-617a0bdf-b7f0-4698-b8eb-eeaa20b8f4d1' class='xr-index-data-in' type='checkbox'/><label for='index-617a0bdf-b7f0-4698-b8eb-eeaa20b8f4d1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -90.0, -88.75,  -87.5, -86.25,  -85.0, -83.75,  -82.5, -81.25,  -80.0,\n",
+       "       -78.75,\n",
+       "       ...\n",
+       "        78.75,   80.0,  81.25,   82.5,  83.75,   85.0,  86.25,   87.5,  88.75,\n",
+       "         90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=145))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0c36c3db-e36f-4aa6-b846-36d9887cc156' class='xr-index-data-in' type='checkbox'/><label for='index-0c36c3db-e36f-4aa6-b846-36d9887cc156' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([    0.0,   1.875,    3.75,   5.625,     7.5,   9.375,   11.25,  13.125,\n",
+       "          15.0,  16.875,\n",
+       "       ...\n",
+       "        341.25, 343.125,   345.0, 346.875,  348.75, 350.625,   352.5, 354.375,\n",
+       "        356.25, 358.125],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-243d501c-b2f8-4b8d-96f8-caf01a52b2f0' class='xr-index-data-in' type='checkbox'/><label for='index-243d501c-b2f8-4b8d-96f8-caf01a52b2f0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-16 12:00:00, 1850-02-15 00:00:00, 1850-03-16 12:00:00,\n",
+       "             1850-04-16 00:00:00, 1850-05-16 12:00:00, 1850-06-16 00:00:00,\n",
+       "             1850-07-16 12:00:00, 1850-08-16 12:00:00, 1850-09-16 00:00:00,\n",
+       "             1850-10-16 12:00:00,\n",
+       "             ...\n",
+       "             2014-03-16 12:00:00, 2014-04-16 00:00:00, 2014-05-16 12:00:00,\n",
+       "             2014-06-16 00:00:00, 2014-07-16 12:00:00, 2014-08-16 12:00:00,\n",
+       "             2014-09-16 00:00:00, 2014-10-16 12:00:00, 2014-11-16 00:00:00,\n",
+       "             2014-12-16 12:00:00],\n",
+       "            dtype=&#x27;object&#x27;,\n",
+       "            length=1980,\n",
+       "            calendar=&#x27;proleptic_gregorian&#x27;,\n",
+       "            freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-66621b41-3f73-4ba9-855c-eb5a19727930' class='xr-section-summary-in' type='checkbox'  ><label for='section-66621b41-3f73-4ba9-855c-eb5a19727930' class='xr-section-summary' >Attributes: <span>(48)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>0.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>87658.0</dd><dt><span>creation_date :</span></dt><dd>2020-06-05T04:06:11Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.30</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.CSIRO.ACCESS-ESM1-5.historical.none.r10i1p1f1</dd><dt><span>grid :</span></dt><dd>native atmosphere N96 grid (145x192 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>history :</span></dt><dd>2020-06-05T04:06:11Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 CMIP-6.2 and CF standards.</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia</dd><dt><span>institution_id :</span></dt><dd>CSIRO</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>nominal_resolution :</span></dt><dd>250 km</dd><dt><span>notes :</span></dt><dd>Exp: ESM-historical; Local ID: HI-14; Variable: tas ([&#x27;fld_s03i236&#x27;])</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>ACCESS-ESM1-5</dd><dt><span>parent_time_units :</span></dt><dd>days since 0101-1-1</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>10</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>run_variant :</span></dt><dd>forcing: GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4, CFC11, CFC12, CFC113, HCFC22, HFC125, HFC134a)</dd><dt><span>source :</span></dt><dd>ACCESS-ESM1.5 (2019): \n",
        "aerosol: CLASSIC (v1.0)\n",
        "atmos: HadGAM2 (r1.1, N96; 192 x 145 longitude/latitude; 38 levels; top level 39255 m)\n",
        "atmosChem: none\n",
@@ -1691,19 +1744,19 @@
        "seaIce: CICE4.1 (same grid as ocean)</dd><dt><span>source_id :</span></dt><dd>ACCESS-ESM1-5</dd><dt><span>source_type :</span></dt><dd>AOGCM</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>Amon</dd><dt><span>table_info :</span></dt><dd>Creation Date:(30 April 2019) MD5:5bd755e94c2173cb3050a0f3480f60c4</dd><dt><span>title :</span></dt><dd>ACCESS-ESM1-5 output prepared for CMIP6</dd><dt><span>variable_id :</span></dt><dd>tas</dd><dt><span>variant_label :</span></dt><dd>r10i1p1f1</dd><dt><span>version :</span></dt><dd>v20200605</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by CSIRO is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment.  Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file). The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.4.0</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/af78ae5e-f3a6-4e99-8cfe-5f29eb467cd1</dd><dt><span>DODS_EXTRA.Unlimited_Dimension :</span></dt><dd>time</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
-       "<xarray.Dataset>\n",
+       "<xarray.Dataset> Size: 221MB\n",
        "Dimensions:    (time: 1980, bnds: 2, lat: 145, lon: 192)\n",
        "Coordinates:\n",
-       "  * time       (time) datetime64[ns] 1850-01-16T12:00:00 ... 2014-12-16T12:00:00\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 ... 352.5 354.4 356.2 358.1\n",
-       "    height     float64 2.0\n",
+       "  * lat        (lat) float64 1kB -90.0 -88.75 -87.5 -86.25 ... 87.5 88.75 90.0\n",
+       "  * lon        (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 354.4 356.2 358.1\n",
+       "    height     float64 8B 2.0\n",
+       "  * time       (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:00:00\n",
        "Dimensions without coordinates: bnds\n",
        "Data variables:\n",
-       "    time_bnds  (time, bnds) datetime64[ns] ...\n",
-       "    lat_bnds   (lat, bnds) float64 ...\n",
-       "    lon_bnds   (lon, bnds) float64 ...\n",
-       "    tas        (time, lat, lon) float32 -27.19 -27.19 -27.19 ... -25.29 -25.29\n",
+       "    time_bnds  (time, bnds) object 32kB ...\n",
+       "    lat_bnds   (lat, bnds) float64 2kB ...\n",
+       "    lon_bnds   (lon, bnds) float64 3kB ...\n",
+       "    tas        (time, lat, lon) float32 220MB -27.19 -27.19 ... -25.29 -25.29\n",
        "Attributes: (12/48)\n",
        "    Conventions:                     CF-1.7 CMIP-6.2\n",
        "    activity_id:                     CMIP\n",
@@ -2022,6 +2075,11 @@
        "  grid-column: 4;\n",
        "}\n",
        "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
        ".xr-var-name,\n",
        ".xr-var-dims,\n",
        ".xr-var-dtype,\n",
@@ -2043,14 +2101,16 @@
        "}\n",
        "\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-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",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
        "  display: block;\n",
        "}\n",
        "\n",
@@ -2060,13 +2120,16 @@
        "\n",
        ".xr-var-name span,\n",
        ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
        ".xr-attrs {\n",
        "  padding-left: 25px !important;\n",
        "}\n",
        "\n",
        ".xr-attrs,\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
        "  grid-column: 1 / -1;\n",
        "}\n",
        "\n",
@@ -2104,7 +2167,8 @@
        "}\n",
        "\n",
        ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
        "  display: inline-block;\n",
        "  vertical-align: middle;\n",
        "  width: 1em;\n",
@@ -2113,7 +2177,7 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tas&#x27; (time: 165, lat: 145, lon: 192)&gt;\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tas&#x27; (time: 165, lat: 145, lon: 192)&gt; Size: 37MB\n",
        "array([[[-48.75573349, -48.75573349, -48.75573349, ..., -48.75573349,\n",
        "         -48.75573349, -48.75573349],\n",
        "        [-45.65206528, -45.69302368, -45.73506165, ..., -45.52127838,\n",
@@ -2156,15 +2220,15 @@
        "        [-15.6184063 , -15.6184063 , -15.6184063 , ..., -15.6184063 ,\n",
        "         -15.6184063 , -15.6184063 ]]])\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",
-       "    height   float64 2.0\n",
-       "  * time     (time) object 1850-01-01 00:00:00 ... 2014-01-01 00:00:00\n",
+       "  * lat      (lat) float64 1kB -90.0 -88.75 -87.5 -86.25 ... 87.5 88.75 90.0\n",
+       "  * lon      (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 352.5 354.4 356.2 358.1\n",
+       "    height   float64 8B 2.0\n",
+       "  * time     (time) object 1kB 1850-01-01 00:00:00 ... 2014-01-01 00:00:00\n",
        "Attributes:\n",
        "    operation:  temporal_avg\n",
        "    mode:       group_average\n",
        "    freq:       year\n",
-       "    weighted:   True</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'tas'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 165</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-4a74978e-2832-4b21-a535-1cf65e919a67' class='xr-array-in' type='checkbox' checked><label for='section-4a74978e-2832-4b21-a535-1cf65e919a67' 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>-48.76 -48.76 -48.76 -48.76 -48.76 ... -15.62 -15.62 -15.62 -15.62</span></div><div class='xr-array-data'><pre>array([[[-48.75573349, -48.75573349, -48.75573349, ..., -48.75573349,\n",
+       "    weighted:   True</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'tas'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 165</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-67308fa7-a39b-4c72-9f66-73882099b027' class='xr-array-in' type='checkbox' checked><label for='section-67308fa7-a39b-4c72-9f66-73882099b027' 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>-48.76 -48.76 -48.76 -48.76 -48.76 ... -15.62 -15.62 -15.62 -15.62</span></div><div class='xr-array-data'><pre>array([[[-48.75573349, -48.75573349, -48.75573349, ..., -48.75573349,\n",
        "         -48.75573349, -48.75573349],\n",
        "        [-45.65206528, -45.69302368, -45.73506165, ..., -45.52127838,\n",
        "         -45.56386566, -45.60668945],\n",
@@ -2204,7 +2268,7 @@
        "        [-14.91123581, -14.89230919, -14.86901569, ..., -14.9820118 ,\n",
        "         -14.96266842, -14.93872261],\n",
        "        [-15.6184063 , -15.6184063 , -15.6184063 , ..., -15.6184063 ,\n",
-       "         -15.6184063 , -15.6184063 ]]])</pre></div></div></li><li class='xr-section-item'><input id='section-e6d4d4ef-a729-40b1-9920-b25d11b30203' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e6d4d4ef-a729-40b1-9920-b25d11b30203' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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-f4539990-14c5-4f58-908f-d5742cf2fabf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f4539990-14c5-4f58-908f-d5742cf2fabf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60db3f66-2c62-475d-837e-2b232b4bc0e6' class='xr-var-data-in' type='checkbox'><label for='data-60db3f66-2c62-475d-837e-2b232b4bc0e6' 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",
+       "         -15.6184063 , -15.6184063 ]]])</pre></div></div></li><li class='xr-section-item'><input id='section-307c0814-8064-43b9-afdd-589a7546326d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-307c0814-8064-43b9-afdd-589a7546326d' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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-d9d01e86-6e87-4fc8-9f59-4433efa781dc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d9d01e86-6e87-4fc8-9f59-4433efa781dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f526631-4071-4bf4-bfe9-f5a4a35b92b8' class='xr-var-data-in' type='checkbox'><label for='data-7f526631-4071-4bf4-bfe9-f5a4a35b92b8' 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",
@@ -2220,7 +2284,7 @@
        "        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-9414c84a-92b1-42fa-82c2-9e3aafe12cbc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9414c84a-92b1-42fa-82c2-9e3aafe12cbc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ff78fa0-f271-4080-a093-66ab70f6f504' class='xr-var-data-in' type='checkbox'><label for='data-8ff78fa0-f271-4080-a093-66ab70f6f504' 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",
+       "        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-acbdfad3-ba82-4a26-9daf-d8911a1544a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-acbdfad3-ba82-4a26-9daf-d8911a1544a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6a1fc14-94fe-40ab-87c0-386d36f46eff' class='xr-var-data-in' type='checkbox'><label for='data-e6a1fc14-94fe-40ab-87c0-386d36f46eff' 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",
@@ -2243,7 +2307,7 @@
        "       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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-1b9eef88-9a52-47c1-bb8c-42b10ef990dc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b9eef88-9a52-47c1-bb8c-42b10ef990dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1fe4ea35-bcf7-4185-a2ce-883c2221a9d8' class='xr-var-data-in' type='checkbox'><label for='data-1fe4ea35-bcf7-4185-a2ce-883c2221a9d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</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'>object</div><div class='xr-var-preview xr-preview'>1850-01-01 00:00:00 ... 2014-01-...</div><input id='attrs-b11ceab4-79a9-4792-8654-5c2032f3dc6b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b11ceab4-79a9-4792-8654-5c2032f3dc6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-826162a6-1761-4982-b12b-88ddce790921' class='xr-var-data-in' type='checkbox'><label for='data-826162a6-1761-4982-b12b-88ddce790921' 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><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeProlepticGregorian(1850, 1, 1, 0, 0, 0, 0, has_year_zero=True),\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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-3e6df02b-76ba-4c4d-8bcc-8eb5f0bd3743' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e6df02b-76ba-4c4d-8bcc-8eb5f0bd3743' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54f2b6cf-0b14-42f4-8822-e9b575e05f7c' class='xr-var-data-in' type='checkbox'><label for='data-54f2b6cf-0b14-42f4-8822-e9b575e05f7c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</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'>object</div><div class='xr-var-preview xr-preview'>1850-01-01 00:00:00 ... 2014-01-...</div><input id='attrs-77da6fb0-80b4-494c-b8a6-9cc118797961' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-77da6fb0-80b4-494c-b8a6-9cc118797961' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c77fb89b-2c2d-4146-8ab1-28d09aee40c7' class='xr-var-data-in' type='checkbox'><label for='data-c77fb89b-2c2d-4146-8ab1-28d09aee40c7' 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><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeProlepticGregorian(1850, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(1851, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(1852, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(1853, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
@@ -2408,10 +2472,32 @@
        "       cftime.DatetimeProlepticGregorian(2012, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(2013, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(2014, 1, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
-       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ccccf543-20ef-451d-bd40-9fe93d1c99fc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ccccf543-20ef-451d-bd40-9fe93d1c99fc' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><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>year</dd><dt><span>weighted :</span></dt><dd>True</dd></dl></div></li></ul></div></div>"
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-44ad1151-cd63-4871-9fe6-2365af2dac49' class='xr-section-summary-in' type='checkbox'  ><label for='section-44ad1151-cd63-4871-9fe6-2365af2dac49' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f9c275a8-9ff5-4dcb-b3d6-7703eaa37074' class='xr-index-data-in' type='checkbox'/><label for='index-f9c275a8-9ff5-4dcb-b3d6-7703eaa37074' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -90.0, -88.75,  -87.5, -86.25,  -85.0, -83.75,  -82.5, -81.25,  -80.0,\n",
+       "       -78.75,\n",
+       "       ...\n",
+       "        78.75,   80.0,  81.25,   82.5,  83.75,   85.0,  86.25,   87.5,  88.75,\n",
+       "         90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=145))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-85a0237a-2aac-4250-a0af-ee0eb05fb8ec' class='xr-index-data-in' type='checkbox'/><label for='index-85a0237a-2aac-4250-a0af-ee0eb05fb8ec' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([    0.0,   1.875,    3.75,   5.625,     7.5,   9.375,   11.25,  13.125,\n",
+       "          15.0,  16.875,\n",
+       "       ...\n",
+       "        341.25, 343.125,   345.0, 346.875,  348.75, 350.625,   352.5, 354.375,\n",
+       "        356.25, 358.125],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8a6c353c-f69f-4ede-8fd1-b458a62952e0' class='xr-index-data-in' type='checkbox'/><label for='index-8a6c353c-f69f-4ede-8fd1-b458a62952e0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-01 00:00:00, 1851-01-01 00:00:00, 1852-01-01 00:00:00,\n",
+       "             1853-01-01 00:00:00, 1854-01-01 00:00:00, 1855-01-01 00:00:00,\n",
+       "             1856-01-01 00:00:00, 1857-01-01 00:00:00, 1858-01-01 00:00:00,\n",
+       "             1859-01-01 00:00:00,\n",
+       "             ...\n",
+       "             2005-01-01 00:00:00, 2006-01-01 00:00:00, 2007-01-01 00:00:00,\n",
+       "             2008-01-01 00:00:00, 2009-01-01 00:00:00, 2010-01-01 00:00:00,\n",
+       "             2011-01-01 00:00:00, 2012-01-01 00:00:00, 2013-01-01 00:00:00,\n",
+       "             2014-01-01 00:00:00],\n",
+       "            dtype=&#x27;object&#x27;,\n",
+       "            length=165,\n",
+       "            calendar=&#x27;proleptic_gregorian&#x27;,\n",
+       "            freq=&#x27;YS-JAN&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-83599b4f-15a1-45ab-8a4f-804dfdf8e2cf' class='xr-section-summary-in' type='checkbox'  checked><label for='section-83599b4f-15a1-45ab-8a4f-804dfdf8e2cf' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><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>year</dd><dt><span>weighted :</span></dt><dd>True</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
-       "<xarray.DataArray 'tas' (time: 165, lat: 145, lon: 192)>\n",
+       "<xarray.DataArray 'tas' (time: 165, lat: 145, lon: 192)> Size: 37MB\n",
        "array([[[-48.75573349, -48.75573349, -48.75573349, ..., -48.75573349,\n",
        "         -48.75573349, -48.75573349],\n",
        "        [-45.65206528, -45.69302368, -45.73506165, ..., -45.52127838,\n",
@@ -2454,10 +2540,10 @@
        "        [-15.6184063 , -15.6184063 , -15.6184063 , ..., -15.6184063 ,\n",
        "         -15.6184063 , -15.6184063 ]]])\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",
-       "    height   float64 2.0\n",
-       "  * time     (time) object 1850-01-01 00:00:00 ... 2014-01-01 00:00:00\n",
+       "  * lat      (lat) float64 1kB -90.0 -88.75 -87.5 -86.25 ... 87.5 88.75 90.0\n",
+       "  * lon      (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 352.5 354.4 356.2 358.1\n",
+       "    height   float64 8B 2.0\n",
+       "  * time     (time) object 1kB 1850-01-01 00:00:00 ... 2014-01-01 00:00:00\n",
        "Attributes:\n",
        "    operation:  temporal_avg\n",
        "    mode:       group_average\n",
@@ -2778,6 +2864,11 @@
        "  grid-column: 4;\n",
        "}\n",
        "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
        ".xr-var-name,\n",
        ".xr-var-dims,\n",
        ".xr-var-dtype,\n",
@@ -2799,14 +2890,16 @@
        "}\n",
        "\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-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",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
        "  display: block;\n",
        "}\n",
        "\n",
@@ -2816,13 +2909,16 @@
        "\n",
        ".xr-var-name span,\n",
        ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
        ".xr-attrs {\n",
        "  padding-left: 25px !important;\n",
        "}\n",
        "\n",
        ".xr-attrs,\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
        "  grid-column: 1 / -1;\n",
        "}\n",
        "\n",
@@ -2860,7 +2956,8 @@
        "}\n",
        "\n",
        ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
        "  display: inline-block;\n",
        "  vertical-align: middle;\n",
        "  width: 1em;\n",
@@ -2869,7 +2966,7 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tas&#x27; (time: 661, lat: 145, lon: 192)&gt;\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tas&#x27; (time: 661, lat: 145, lon: 192)&gt; Size: 147MB\n",
        "array([[[-32.70588303, -32.70588303, -32.70588303, ..., -32.70588303,\n",
        "         -32.70588303, -32.70588303],\n",
        "        [-30.99376678, -31.03758621, -31.08932686, ..., -30.84562302,\n",
@@ -2912,17 +3009,17 @@
        "        [-25.28923035, -25.28923035, -25.28923035, ..., -25.28923035,\n",
        "         -25.28923035, -25.28923035]]])\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",
-       "    height   float64 2.0\n",
-       "  * time     (time) object 1850-01-01 00:00:00 ... 2015-01-01 00:00:00\n",
+       "  * lat      (lat) float64 1kB -90.0 -88.75 -87.5 -86.25 ... 87.5 88.75 90.0\n",
+       "  * lon      (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 352.5 354.4 356.2 358.1\n",
+       "    height   float64 8B 2.0\n",
+       "  * time     (time) object 5kB 1850-01-01 00:00:00 ... 2015-01-01 00:00:00\n",
        "Attributes:\n",
        "    operation:            temporal_avg\n",
        "    mode:                 group_average\n",
        "    freq:                 season\n",
        "    weighted:             True\n",
        "    dec_mode:             DJF\n",
-       "    drop_incomplete_djf:  False</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'tas'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 661</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-89b9a8a0-d53c-458d-abc0-83a6bef510a6' class='xr-array-in' type='checkbox' checked><label for='section-89b9a8a0-d53c-458d-abc0-83a6bef510a6' 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>-32.71 -32.71 -32.71 -32.71 -32.71 ... -25.29 -25.29 -25.29 -25.29</span></div><div class='xr-array-data'><pre>array([[[-32.70588303, -32.70588303, -32.70588303, ..., -32.70588303,\n",
+       "    drop_incomplete_djf:  False</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'tas'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 661</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-10accefc-0322-45ff-a16c-e3b0cb5b65a9' class='xr-array-in' type='checkbox' checked><label for='section-10accefc-0322-45ff-a16c-e3b0cb5b65a9' 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>-32.71 -32.71 -32.71 -32.71 -32.71 ... -25.29 -25.29 -25.29 -25.29</span></div><div class='xr-array-data'><pre>array([[[-32.70588303, -32.70588303, -32.70588303, ..., -32.70588303,\n",
        "         -32.70588303, -32.70588303],\n",
        "        [-30.99376678, -31.03758621, -31.08932686, ..., -30.84562302,\n",
        "         -30.89412689, -30.94400978],\n",
@@ -2962,7 +3059,7 @@
        "        [-24.62901306, -24.61338806, -24.54986572, ..., -24.75204468,\n",
        "         -24.72160339, -24.66641235],\n",
        "        [-25.28923035, -25.28923035, -25.28923035, ..., -25.28923035,\n",
-       "         -25.28923035, -25.28923035]]])</pre></div></div></li><li class='xr-section-item'><input id='section-f01e66db-9c90-4ebe-a081-db578e89fc68' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f01e66db-9c90-4ebe-a081-db578e89fc68' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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-719cc788-4358-49fc-afe4-41e08507683e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-719cc788-4358-49fc-afe4-41e08507683e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8109dcc1-d41e-4d0a-bfa0-2fd59d53fa3b' class='xr-var-data-in' type='checkbox'><label for='data-8109dcc1-d41e-4d0a-bfa0-2fd59d53fa3b' 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",
+       "         -25.28923035, -25.28923035]]])</pre></div></div></li><li class='xr-section-item'><input id='section-a9ffb522-8d34-4ee8-bbc7-a7ca7b5f728c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a9ffb522-8d34-4ee8-bbc7-a7ca7b5f728c' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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-6c79cca8-0ee4-47b4-b464-0b6bc1d015a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c79cca8-0ee4-47b4-b464-0b6bc1d015a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac0efdbf-af21-4cd5-ad28-24ea869f2751' class='xr-var-data-in' type='checkbox'><label for='data-ac0efdbf-af21-4cd5-ad28-24ea869f2751' 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",
@@ -2978,7 +3075,7 @@
        "        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-a206c1a7-7004-4a54-87a0-161e2b1c4d2b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a206c1a7-7004-4a54-87a0-161e2b1c4d2b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5b80494-dc84-46d5-95b4-27814364fbe2' class='xr-var-data-in' type='checkbox'><label for='data-c5b80494-dc84-46d5-95b4-27814364fbe2' 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",
+       "        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-36aceb10-32b1-4590-96d4-bfa0c46dfb55' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36aceb10-32b1-4590-96d4-bfa0c46dfb55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a41726b-5ab3-4308-9b94-8b79f3cc6830' class='xr-var-data-in' type='checkbox'><label for='data-5a41726b-5ab3-4308-9b94-8b79f3cc6830' 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",
@@ -3001,17 +3098,39 @@
        "       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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-0054093f-f484-4f42-863b-b5eb034e71a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0054093f-f484-4f42-863b-b5eb034e71a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d30f7276-53b2-4133-a9c8-8660a1d86f9d' class='xr-var-data-in' type='checkbox'><label for='data-d30f7276-53b2-4133-a9c8-8660a1d86f9d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</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'>object</div><div class='xr-var-preview xr-preview'>1850-01-01 00:00:00 ... 2015-01-...</div><input id='attrs-8f608d8b-93db-4502-a412-4965323c932e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f608d8b-93db-4502-a412-4965323c932e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b06bb81-1e35-4944-8aff-0dada4f6d0fe' class='xr-var-data-in' type='checkbox'><label for='data-5b06bb81-1e35-4944-8aff-0dada4f6d0fe' 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><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeProlepticGregorian(1850, 1, 1, 0, 0, 0, 0, has_year_zero=True),\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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-faee9ce4-0942-420b-9b4f-2bf0bf11d3b2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-faee9ce4-0942-420b-9b4f-2bf0bf11d3b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ccf6e25d-1425-4202-bd97-73c0c97c3a42' class='xr-var-data-in' type='checkbox'><label for='data-ccf6e25d-1425-4202-bd97-73c0c97c3a42' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</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'>object</div><div class='xr-var-preview xr-preview'>1850-01-01 00:00:00 ... 2015-01-...</div><input id='attrs-8b935383-03dc-4740-8a45-d7c763d7d39c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8b935383-03dc-4740-8a45-d7c763d7d39c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cde76706-6e6c-4bb2-b308-965b3f774b2e' class='xr-var-data-in' type='checkbox'><label for='data-cde76706-6e6c-4bb2-b308-965b3f774b2e' 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><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeProlepticGregorian(1850, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(1850, 4, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(1850, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       ...,\n",
        "       cftime.DatetimeProlepticGregorian(2014, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(2014, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(2015, 1, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
-       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7a678a94-29ab-4ad2-b175-0a8060a242b9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7a678a94-29ab-4ad2-b175-0a8060a242b9' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><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>dec_mode :</span></dt><dd>DJF</dd><dt><span>drop_incomplete_djf :</span></dt><dd>False</dd></dl></div></li></ul></div></div>"
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7200d624-17f1-405d-840a-4ddd8a34c2b5' class='xr-section-summary-in' type='checkbox'  ><label for='section-7200d624-17f1-405d-840a-4ddd8a34c2b5' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bc318f46-1b7e-4d14-b822-9f7850a71ff1' class='xr-index-data-in' type='checkbox'/><label for='index-bc318f46-1b7e-4d14-b822-9f7850a71ff1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -90.0, -88.75,  -87.5, -86.25,  -85.0, -83.75,  -82.5, -81.25,  -80.0,\n",
+       "       -78.75,\n",
+       "       ...\n",
+       "        78.75,   80.0,  81.25,   82.5,  83.75,   85.0,  86.25,   87.5,  88.75,\n",
+       "         90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=145))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-858958e5-7618-4c3d-8f64-9a34ff2422af' class='xr-index-data-in' type='checkbox'/><label for='index-858958e5-7618-4c3d-8f64-9a34ff2422af' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([    0.0,   1.875,    3.75,   5.625,     7.5,   9.375,   11.25,  13.125,\n",
+       "          15.0,  16.875,\n",
+       "       ...\n",
+       "        341.25, 343.125,   345.0, 346.875,  348.75, 350.625,   352.5, 354.375,\n",
+       "        356.25, 358.125],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7ac49bd8-5b4f-4292-9b41-a8c75aa9bef6' class='xr-index-data-in' type='checkbox'/><label for='index-7ac49bd8-5b4f-4292-9b41-a8c75aa9bef6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-01 00:00:00, 1850-04-01 00:00:00, 1850-07-01 00:00:00,\n",
+       "             1850-10-01 00:00:00, 1851-01-01 00:00:00, 1851-04-01 00:00:00,\n",
+       "             1851-07-01 00:00:00, 1851-10-01 00:00:00, 1852-01-01 00:00:00,\n",
+       "             1852-04-01 00:00:00,\n",
+       "             ...\n",
+       "             2012-10-01 00:00:00, 2013-01-01 00:00:00, 2013-04-01 00:00:00,\n",
+       "             2013-07-01 00:00:00, 2013-10-01 00:00:00, 2014-01-01 00:00:00,\n",
+       "             2014-04-01 00:00:00, 2014-07-01 00:00:00, 2014-10-01 00:00:00,\n",
+       "             2015-01-01 00:00:00],\n",
+       "            dtype=&#x27;object&#x27;,\n",
+       "            length=661,\n",
+       "            calendar=&#x27;proleptic_gregorian&#x27;,\n",
+       "            freq=&#x27;QS-OCT&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-81e3dac5-8cf0-4231-a0dc-69b1eac2a266' class='xr-section-summary-in' type='checkbox'  checked><label for='section-81e3dac5-8cf0-4231-a0dc-69b1eac2a266' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><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>dec_mode :</span></dt><dd>DJF</dd><dt><span>drop_incomplete_djf :</span></dt><dd>False</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
-       "<xarray.DataArray 'tas' (time: 661, lat: 145, lon: 192)>\n",
+       "<xarray.DataArray 'tas' (time: 661, lat: 145, lon: 192)> Size: 147MB\n",
        "array([[[-32.70588303, -32.70588303, -32.70588303, ..., -32.70588303,\n",
        "         -32.70588303, -32.70588303],\n",
        "        [-30.99376678, -31.03758621, -31.08932686, ..., -30.84562302,\n",
@@ -3054,10 +3173,10 @@
        "        [-25.28923035, -25.28923035, -25.28923035, ..., -25.28923035,\n",
        "         -25.28923035, -25.28923035]]])\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",
-       "    height   float64 2.0\n",
-       "  * time     (time) object 1850-01-01 00:00:00 ... 2015-01-01 00:00:00\n",
+       "  * lat      (lat) float64 1kB -90.0 -88.75 -87.5 -86.25 ... 87.5 88.75 90.0\n",
+       "  * lon      (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 352.5 354.4 356.2 358.1\n",
+       "    height   float64 8B 2.0\n",
+       "  * time     (time) object 5kB 1850-01-01 00:00:00 ... 2015-01-01 00:00:00\n",
        "Attributes:\n",
        "    operation:            temporal_avg\n",
        "    mode:                 group_average\n",
@@ -3359,6 +3478,11 @@
        "  grid-column: 4;\n",
        "}\n",
        "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
        ".xr-var-name,\n",
        ".xr-var-dims,\n",
        ".xr-var-dtype,\n",
@@ -3380,14 +3504,16 @@
        "}\n",
        "\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-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",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
        "  display: block;\n",
        "}\n",
        "\n",
@@ -3397,13 +3523,16 @@
        "\n",
        ".xr-var-name span,\n",
        ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
        ".xr-attrs {\n",
        "  padding-left: 25px !important;\n",
        "}\n",
        "\n",
        ".xr-attrs,\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
        "  grid-column: 1 / -1;\n",
        "}\n",
        "\n",
@@ -3441,7 +3570,8 @@
        "}\n",
        "\n",
        ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
        "  display: inline-block;\n",
        "  vertical-align: middle;\n",
        "  width: 1em;\n",
@@ -3450,7 +3580,7 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;time&#x27; (time: 661)&gt;\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;time&#x27; (time: 661)&gt; Size: 5kB\n",
        "array([cftime.DatetimeProlepticGregorian(1850, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(1850, 4, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(1850, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
@@ -3460,31 +3590,43 @@
        "       cftime.DatetimeProlepticGregorian(2015, 1, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
        "      dtype=object)\n",
        "Coordinates:\n",
-       "    height   float64 2.0\n",
-       "  * time     (time) object 1850-01-01 00:00:00 ... 2015-01-01 00:00:00\n",
+       "    height   float64 8B 2.0\n",
+       "  * time     (time) object 5kB 1850-01-01 00:00:00 ... 2015-01-01 00:00:00\n",
        "Attributes:\n",
        "    bounds:         time_bnds\n",
        "    axis:           T\n",
        "    long_name:      time\n",
        "    standard_name:  time\n",
-       "    _ChunkSizes:    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'>'time'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 661</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-c37d5292-0b70-4d35-b6fd-7970eae0658d' class='xr-array-in' type='checkbox' checked><label for='section-c37d5292-0b70-4d35-b6fd-7970eae0658d' 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>1850-01-01 00:00:00 1850-04-01 00:00:00 ... 2015-01-01 00:00:00</span></div><div class='xr-array-data'><pre>array([cftime.DatetimeProlepticGregorian(1850, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
+       "    _ChunkSizes:    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'>'time'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 661</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-2e85201e-4915-4bf6-b69b-96e8294e4d2c' class='xr-array-in' type='checkbox' checked><label for='section-2e85201e-4915-4bf6-b69b-96e8294e4d2c' 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>1850-01-01 00:00:00 1850-04-01 00:00:00 ... 2015-01-01 00:00:00</span></div><div class='xr-array-data'><pre>array([cftime.DatetimeProlepticGregorian(1850, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(1850, 4, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(1850, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       ...,\n",
        "       cftime.DatetimeProlepticGregorian(2014, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(2014, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(2015, 1, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
-       "      dtype=object)</pre></div></div></li><li class='xr-section-item'><input id='section-3b29a5c4-18a7-426b-a669-fe1da8343919' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3b29a5c4-18a7-426b-a669-fe1da8343919' 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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-d45542ef-f0b6-4e67-82b1-9a0836817d55' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d45542ef-f0b6-4e67-82b1-9a0836817d55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f37b951b-655b-429f-9088-b25e257548ee' class='xr-var-data-in' type='checkbox'><label for='data-f37b951b-655b-429f-9088-b25e257548ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</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'>object</div><div class='xr-var-preview xr-preview'>1850-01-01 00:00:00 ... 2015-01-...</div><input id='attrs-b671f7d6-637b-4669-bfa7-4796ab6e70a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b671f7d6-637b-4669-bfa7-4796ab6e70a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d37079ef-f0ea-4841-8c41-09c18eea0119' class='xr-var-data-in' type='checkbox'><label for='data-d37079ef-f0ea-4841-8c41-09c18eea0119' 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><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeProlepticGregorian(1850, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
+       "      dtype=object)</pre></div></div></li><li class='xr-section-item'><input id='section-919a3813-174f-4c30-a270-3c061f72d4f9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-919a3813-174f-4c30-a270-3c061f72d4f9' 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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-e81f99b9-6fd9-4d1e-9cf8-d9ddda39c096' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e81f99b9-6fd9-4d1e-9cf8-d9ddda39c096' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-934bda2f-a218-4f99-b056-60f846718874' class='xr-var-data-in' type='checkbox'><label for='data-934bda2f-a218-4f99-b056-60f846718874' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</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'>object</div><div class='xr-var-preview xr-preview'>1850-01-01 00:00:00 ... 2015-01-...</div><input id='attrs-f8c4e3f2-4518-4a3d-8cbb-cd90f4a0974d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f8c4e3f2-4518-4a3d-8cbb-cd90f4a0974d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a6d514a-0df5-41bf-af04-7d4aed5ed379' class='xr-var-data-in' type='checkbox'><label for='data-5a6d514a-0df5-41bf-af04-7d4aed5ed379' 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><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeProlepticGregorian(1850, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(1850, 4, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(1850, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       ...,\n",
        "       cftime.DatetimeProlepticGregorian(2014, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(2014, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(2015, 1, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
-       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-98533a79-00fe-4474-a9f8-b692e7c9f2ff' class='xr-section-summary-in' type='checkbox'  checked><label for='section-98533a79-00fe-4474-a9f8-b692e7c9f2ff' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><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><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div></li></ul></div></div>"
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d985cdfc-fc47-49cd-86f2-cfea82dfcb76' class='xr-section-summary-in' type='checkbox'  ><label for='section-d985cdfc-fc47-49cd-86f2-cfea82dfcb76' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0ab80f26-3ab8-478e-81b8-dae27858beca' class='xr-index-data-in' type='checkbox'/><label for='index-0ab80f26-3ab8-478e-81b8-dae27858beca' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-01 00:00:00, 1850-04-01 00:00:00, 1850-07-01 00:00:00,\n",
+       "             1850-10-01 00:00:00, 1851-01-01 00:00:00, 1851-04-01 00:00:00,\n",
+       "             1851-07-01 00:00:00, 1851-10-01 00:00:00, 1852-01-01 00:00:00,\n",
+       "             1852-04-01 00:00:00,\n",
+       "             ...\n",
+       "             2012-10-01 00:00:00, 2013-01-01 00:00:00, 2013-04-01 00:00:00,\n",
+       "             2013-07-01 00:00:00, 2013-10-01 00:00:00, 2014-01-01 00:00:00,\n",
+       "             2014-04-01 00:00:00, 2014-07-01 00:00:00, 2014-10-01 00:00:00,\n",
+       "             2015-01-01 00:00:00],\n",
+       "            dtype=&#x27;object&#x27;,\n",
+       "            length=661,\n",
+       "            calendar=&#x27;proleptic_gregorian&#x27;,\n",
+       "            freq=&#x27;QS-OCT&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9f1bb52c-4689-4b9b-b72f-008f8a0b6560' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9f1bb52c-4689-4b9b-b72f-008f8a0b6560' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><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><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
-       "<xarray.DataArray 'time' (time: 661)>\n",
+       "<xarray.DataArray 'time' (time: 661)> Size: 5kB\n",
        "array([cftime.DatetimeProlepticGregorian(1850, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(1850, 4, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(1850, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
@@ -3494,8 +3636,8 @@
        "       cftime.DatetimeProlepticGregorian(2015, 1, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
        "      dtype=object)\n",
        "Coordinates:\n",
-       "    height   float64 2.0\n",
-       "  * time     (time) object 1850-01-01 00:00:00 ... 2015-01-01 00:00:00\n",
+       "    height   float64 8B 2.0\n",
+       "  * time     (time) object 5kB 1850-01-01 00:00:00 ... 2015-01-01 00:00:00\n",
        "Attributes:\n",
        "    bounds:         time_bnds\n",
        "    axis:           T\n",
@@ -3513,6 +3655,56 @@
     "ds_season.time"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Visualize averages derived from monthly data on a specific point\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# plot time series of temporal averages for a specific grid point: seasonal and yearly averages derived from monthly time series\n",
+    "lat_point = 30\n",
+    "lon_point = 30\n",
+    "\n",
+    "start_year = \"2005-01-01\"\n",
+    "end_year = \"2014-12-31\"\n",
+    "\n",
+    "plt.figure(figsize=(10, 3))\n",
+    "ax = plt.subplot()\n",
+    "\n",
+    "ds.tas.sel(lat=lat_point, lon=lon_point, time=slice(start_year, end_year)).plot(\n",
+    "    ax=ax, label=\"monthly (RAW DATA)\", alpha=0.5\n",
+    ")\n",
+    "ds_season.tas.sel(lat=lat_point, lon=lon_point, time=slice(start_year, end_year)).plot(\n",
+    "    ax=ax, label=\"season\", alpha=0.5\n",
+    ")\n",
+    "ds_yearly.tas.sel(lat=lat_point, lon=lon_point, time=slice(start_year, end_year)).plot(\n",
+    "    ax=ax, label=\"yearly\", alpha=0.5\n",
+    ")\n",
+    "\n",
+    "plt.title(\"Seasonal and yearly averages derived from monthly time series\")\n",
+    "\n",
+    "plt.legend()\n",
+    "plt.tight_layout()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -3543,7 +3735,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -3810,6 +4002,11 @@
        "  grid-column: 4;\n",
        "}\n",
        "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
        ".xr-var-name,\n",
        ".xr-var-dims,\n",
        ".xr-var-dtype,\n",
@@ -3831,14 +4028,16 @@
        "}\n",
        "\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-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",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
        "  display: block;\n",
        "}\n",
        "\n",
@@ -3848,13 +4047,16 @@
        "\n",
        ".xr-var-name span,\n",
        ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
        ".xr-attrs {\n",
        "  padding-left: 25px !important;\n",
        "}\n",
        "\n",
        ".xr-attrs,\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
        "  grid-column: 1 / -1;\n",
        "}\n",
        "\n",
@@ -3892,7 +4094,8 @@
        "}\n",
        "\n",
        ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
        "  display: inline-block;\n",
        "  vertical-align: middle;\n",
        "  width: 1em;\n",
@@ -3901,19 +4104,19 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:    (time: 14608, lat: 145, bnds: 2, lon: 192)\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2GB\n",
+       "Dimensions:    (lat: 145, bnds: 2, lon: 192, time: 14608)\n",
        "Coordinates:\n",
-       "  * time       (time) datetime64[ns] 2010-01-01T03:00:00 ... 2015-01-01\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 ... 352.5 354.4 356.2 358.1\n",
-       "    height     float64 ...\n",
+       "  * lat        (lat) float64 1kB -90.0 -88.75 -87.5 -86.25 ... 87.5 88.75 90.0\n",
+       "  * lon        (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 354.4 356.2 358.1\n",
+       "    height     float64 8B ...\n",
+       "  * time       (time) object 117kB 2010-01-01 03:00:00 ... 2015-01-01 00:00:00\n",
        "Dimensions without coordinates: bnds\n",
        "Data variables:\n",
-       "    lat_bnds   (lat, bnds) float64 dask.array&lt;chunksize=(145, 2), meta=np.ndarray&gt;\n",
-       "    lon_bnds   (lon, bnds) float64 dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;\n",
-       "    tas        (time, lat, lon) float32 dask.array&lt;chunksize=(913, 145, 192), meta=np.ndarray&gt;\n",
-       "    time_bnds  (time, bnds) datetime64[ns] 2010-01-01T01:30:00 ... 2015-01-01...\n",
+       "    lat_bnds   (lat, bnds) float64 2kB dask.array&lt;chunksize=(145, 2), meta=np.ndarray&gt;\n",
+       "    lon_bnds   (lon, bnds) float64 3kB dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;\n",
+       "    tas        (time, lat, lon) float32 2GB dask.array&lt;chunksize=(1205, 145, 192), meta=np.ndarray&gt;\n",
+       "    time_bnds  (time, bnds) object 234kB 2010-01-01 03:00:00 ... 2015-01-01 0...\n",
        "Attributes: (12/48)\n",
        "    Conventions:                     CF-1.7 CMIP-6.2\n",
        "    activity_id:                     CMIP\n",
@@ -3927,10 +4130,7 @@
        "    license:                         CMIP6 model data produced by CSIRO is li...\n",
        "    cmor_version:                    3.4.0\n",
        "    tracking_id:                     hdl:21.14100/b79e6a05-c482-46cf-b3b8-83b...\n",
-       "    DODS_EXTRA.Unlimited_Dimension:  time</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-aad120fb-f1f7-4568-a7db-bf5196bd10a1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-aad120fb-f1f7-4568-a7db-bf5196bd10a1' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 14608</li><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-698a650f-a17e-4b85-96bf-4d143bf54c71' class='xr-section-summary-in' type='checkbox'  checked><label for='section-698a650f-a17e-4b85-96bf-4d143bf54c71' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2010-01-01T03:00:00 ... 2015-01-01</div><input id='attrs-56fd5555-d27d-4b79-9dfd-b1eda5e7dfc3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-56fd5555-d27d-4b79-9dfd-b1eda5e7dfc3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5d6fb85-b59b-47ef-936d-c70cecf94cbc' class='xr-var-data-in' type='checkbox'><label for='data-b5d6fb85-b59b-47ef-936d-c70cecf94cbc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2010-01-01T03:00:00.000000000&#x27;, &#x27;2010-01-01T06:00:00.000000000&#x27;,\n",
-       "       &#x27;2010-01-01T09:00:00.000000000&#x27;, ..., &#x27;2014-12-31T18:00:00.000000000&#x27;,\n",
-       "       &#x27;2014-12-31T21:00:00.000000000&#x27;, &#x27;2015-01-01T00:00:00.000000000&#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-d07eb83e-1f3d-466a-a1aa-94cd22597e94' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d07eb83e-1f3d-466a-a1aa-94cd22597e94' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-816871f8-076c-4034-850a-e3220856bf17' class='xr-var-data-in' type='checkbox'><label for='data-816871f8-076c-4034-850a-e3220856bf17' 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",
+       "    DODS_EXTRA.Unlimited_Dimension:  time</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-bdfa4917-4114-43b7-bc6a-742e9e5ad131' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bdfa4917-4114-43b7-bc6a-742e9e5ad131' 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>: 14608</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-61b42fc3-f1af-42f0-bd79-35ab064e02f5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-61b42fc3-f1af-42f0-bd79-35ab064e02f5' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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-f337de09-f4f1-4dc6-8452-7d9de6ce96a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f337de09-f4f1-4dc6-8452-7d9de6ce96a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37b1e8dd-12e1-4528-8903-3a1b677a8d69' class='xr-var-data-in' type='checkbox'><label for='data-37b1e8dd-12e1-4528-8903-3a1b677a8d69' 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",
@@ -3946,7 +4146,7 @@
        "        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-234dbc3e-b6f9-4baf-bbbb-54fa2b080159' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-234dbc3e-b6f9-4baf-bbbb-54fa2b080159' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d68962c-42fa-4615-8837-9c95c42429cf' class='xr-var-data-in' type='checkbox'><label for='data-2d68962c-42fa-4615-8837-9c95c42429cf' 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",
+       "        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-7228b4cd-a995-4919-b65c-73ce6199e7bc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7228b4cd-a995-4919-b65c-73ce6199e7bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f05f146d-2988-4ef4-bbc5-0cd2d5e76d2a' class='xr-var-data-in' type='checkbox'><label for='data-f05f146d-2988-4ef4-bbc5-0cd2d5e76d2a' 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",
@@ -3969,10 +4169,17 @@
        "       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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1179ecd0-40e9-4ac3-b0a4-ed16c9919b05' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1179ecd0-40e9-4ac3-b0a4-ed16c9919b05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d601f0dc-4c2b-41a1-97d6-afc33220451b' class='xr-var-data-in' type='checkbox'><label for='data-d601f0dc-4c2b-41a1-97d6-afc33220451b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9ae90879-8498-4706-af8e-38f8967f64c0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9ae90879-8498-4706-af8e-38f8967f64c0' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(145, 2), meta=np.ndarray&gt;</div><input id='attrs-284ce23b-9351-42bf-acd2-333c9a90f90d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-284ce23b-9351-42bf-acd2-333c9a90f90d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aebfc6c2-69b2-4532-81cb-72c1d433e6c2' class='xr-var-data-in' type='checkbox'><label for='data-aebfc6c2-69b2-4532-81cb-72c1d433e6c2' 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>_ChunkSizes :</span></dt><dd>[145   2]</dd></dl></div><div class='xr-var-data'><table>\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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-53d182a8-fa12-4516-ab39-5c8d9298c30c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-53d182a8-fa12-4516-ab39-5c8d9298c30c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b23f156-9faf-45f7-a6a9-408b727d08a5' class='xr-var-data-in' type='checkbox'><label for='data-8b23f156-9faf-45f7-a6a9-408b727d08a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><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'>2010-01-01 03:00:00 ... 2015-01-...</div><input id='attrs-461bfc7a-6ea5-498e-8281-d4c9081ab5c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-461bfc7a-6ea5-498e-8281-d4c9081ab5c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-74719e7d-0c17-48f7-9ea1-2773f8e504d8' class='xr-var-data-in' type='checkbox'><label for='data-74719e7d-0c17-48f7-9ea1-2773f8e504d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeProlepticGregorian(2010, 1, 1, 3, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeProlepticGregorian(2010, 1, 1, 6, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeProlepticGregorian(2010, 1, 1, 9, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeProlepticGregorian(2014, 12, 31, 18, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeProlepticGregorian(2014, 12, 31, 21, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeProlepticGregorian(2015, 1, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f69b89ea-b51f-4a24-a2cc-200e1ea1b9a8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f69b89ea-b51f-4a24-a2cc-200e1ea1b9a8' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(145, 2), meta=np.ndarray&gt;</div><input id='attrs-825ac0e4-ed64-490a-a509-1e6574726f11' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-825ac0e4-ed64-490a-a509-1e6574726f11' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-979e3e0a-4091-4024-ac92-7c3fda009196' class='xr-var-data-in' type='checkbox'><label for='data-979e3e0a-4091-4024-ac92-7c3fda009196' 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>_ChunkSizes :</span></dt><dd>[145   2]</dd></dl></div><div class='xr-var-data'><table>\n",
        "    <tr>\n",
        "        <td>\n",
-       "            <table>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
        "                <thead>\n",
        "                    <tr>\n",
        "                        <td> </td>\n",
@@ -3994,14 +4201,12 @@
        "                        <td> (145, 2) </td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
-       "                        <th> Count </th>\n",
-       "                        <td> 2 Graph Layers </td>\n",
-       "                        <td> 1 Chunks </td>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
-       "                    <th> Type </th>\n",
-       "                    <td> float64 </td>\n",
-       "                    <td> numpy.ndarray </td>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
        "                    </tr>\n",
        "                </tbody>\n",
        "            </table>\n",
@@ -4026,10 +4231,10 @@
        "</svg>\n",
        "        </td>\n",
        "    </tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;</div><input id='attrs-aa0ea0a4-85b5-4dc6-967c-91f62e4401af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa0ea0a4-85b5-4dc6-967c-91f62e4401af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7340347f-eec4-40a2-9281-09e735627c70' class='xr-var-data-in' type='checkbox'><label for='data-7340347f-eec4-40a2-9281-09e735627c70' 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>_ChunkSizes :</span></dt><dd>[192   2]</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(192, 2), meta=np.ndarray&gt;</div><input id='attrs-8c60a0f1-6b00-4836-9855-d2e775f3e4fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c60a0f1-6b00-4836-9855-d2e775f3e4fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e096b07f-8b07-4231-aa82-567abfb16745' class='xr-var-data-in' type='checkbox'><label for='data-e096b07f-8b07-4231-aa82-567abfb16745' 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>_ChunkSizes :</span></dt><dd>[192   2]</dd></dl></div><div class='xr-var-data'><table>\n",
        "    <tr>\n",
        "        <td>\n",
-       "            <table>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
        "                <thead>\n",
        "                    <tr>\n",
        "                        <td> </td>\n",
@@ -4051,14 +4256,12 @@
        "                        <td> (192, 2) </td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
-       "                        <th> Count </th>\n",
-       "                        <td> 2 Graph Layers </td>\n",
-       "                        <td> 1 Chunks </td>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
-       "                    <th> Type </th>\n",
-       "                    <td> float64 </td>\n",
-       "                    <td> numpy.ndarray </td>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
        "                    </tr>\n",
        "                </tbody>\n",
        "            </table>\n",
@@ -4083,10 +4286,10 @@
        "</svg>\n",
        "        </td>\n",
        "    </tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(913, 145, 192), meta=np.ndarray&gt;</div><input id='attrs-281f107f-0068-4b84-bb83-5beac7de36a5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-281f107f-0068-4b84-bb83-5beac7de36a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ddc93648-b818-4ba8-834c-489c27559700' class='xr-var-data-in' type='checkbox'><label for='data-ddc93648-b818-4ba8-834c-489c27559700' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1205, 145, 192), meta=np.ndarray&gt;</div><input id='attrs-36106d49-70a5-4679-80f9-e51edfc1c880' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-36106d49-70a5-4679-80f9-e51edfc1c880' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c51d50e1-1372-4a9e-b8c4-df901c288bd2' class='xr-var-data-in' type='checkbox'><label for='data-c51d50e1-1372-4a9e-b8c4-df901c288bd2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
        "    <tr>\n",
        "        <td>\n",
-       "            <table>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
        "                <thead>\n",
        "                    <tr>\n",
        "                        <td> </td>\n",
@@ -4099,23 +4302,21 @@
        "                    <tr>\n",
        "                        <th> Bytes </th>\n",
        "                        <td> 1.52 GiB </td>\n",
-       "                        <td> 96.96 MiB </td>\n",
+       "                        <td> 127.97 MiB </td>\n",
        "                    </tr>\n",
        "                    \n",
        "                    <tr>\n",
        "                        <th> Shape </th>\n",
        "                        <td> (14608, 145, 192) </td>\n",
-       "                        <td> (913, 145, 192) </td>\n",
+       "                        <td> (1205, 145, 192) </td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
-       "                        <th> Count </th>\n",
-       "                        <td> 3 Graph Layers </td>\n",
-       "                        <td> 16 Chunks </td>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 13 chunks in 3 graph layers </td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
-       "                    <th> Type </th>\n",
-       "                    <td> float32 </td>\n",
-       "                    <td> numpy.ndarray </td>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
        "                    </tr>\n",
        "                </tbody>\n",
        "            </table>\n",
@@ -4129,21 +4330,18 @@
        "\n",
        "  <!-- Vertical lines -->\n",
        "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"25\" style=\"stroke-width:2\" />\n",
-       "  <line x1=\"14\" y1=\"4\" x2=\"14\" y2=\"29\" />\n",
-       "  <line x1=\"18\" y1=\"8\" x2=\"18\" y2=\"34\" />\n",
-       "  <line x1=\"23\" y1=\"13\" x2=\"23\" y2=\"38\" />\n",
-       "  <line x1=\"27\" y1=\"17\" x2=\"27\" y2=\"43\" />\n",
-       "  <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"47\" />\n",
-       "  <line x1=\"36\" y1=\"26\" x2=\"36\" y2=\"51\" />\n",
-       "  <line x1=\"40\" y1=\"30\" x2=\"40\" y2=\"56\" />\n",
-       "  <line x1=\"45\" y1=\"35\" x2=\"45\" y2=\"60\" />\n",
-       "  <line x1=\"49\" y1=\"39\" x2=\"49\" y2=\"65\" />\n",
-       "  <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"69\" />\n",
-       "  <line x1=\"58\" y1=\"48\" x2=\"58\" y2=\"73\" />\n",
-       "  <line x1=\"62\" y1=\"52\" x2=\"62\" y2=\"78\" />\n",
-       "  <line x1=\"67\" y1=\"57\" x2=\"67\" y2=\"82\" />\n",
-       "  <line x1=\"71\" y1=\"61\" x2=\"71\" y2=\"87\" />\n",
-       "  <line x1=\"76\" y1=\"66\" x2=\"76\" y2=\"91\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"15\" y2=\"31\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"37\" />\n",
+       "  <line x1=\"27\" y1=\"17\" x2=\"27\" y2=\"42\" />\n",
+       "  <line x1=\"33\" y1=\"23\" x2=\"33\" y2=\"48\" />\n",
+       "  <line x1=\"39\" y1=\"29\" x2=\"39\" y2=\"54\" />\n",
+       "  <line x1=\"44\" y1=\"34\" x2=\"44\" y2=\"60\" />\n",
+       "  <line x1=\"50\" y1=\"40\" x2=\"50\" y2=\"66\" />\n",
+       "  <line x1=\"56\" y1=\"46\" x2=\"56\" y2=\"71\" />\n",
+       "  <line x1=\"62\" y1=\"52\" x2=\"62\" y2=\"77\" />\n",
+       "  <line x1=\"68\" y1=\"58\" x2=\"68\" y2=\"83\" />\n",
+       "  <line x1=\"74\" y1=\"64\" x2=\"74\" y2=\"89\" />\n",
+       "  <line x1=\"79\" y1=\"69\" x2=\"79\" y2=\"95\" />\n",
        "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"96\" style=\"stroke-width:2\" />\n",
        "\n",
        "  <!-- Colored Rectangle -->\n",
@@ -4151,21 +4349,18 @@
        "\n",
        "  <!-- Horizontal lines -->\n",
        "  <line x1=\"10\" y1=\"0\" x2=\"36\" y2=\"0\" style=\"stroke-width:2\" />\n",
-       "  <line x1=\"14\" y1=\"4\" x2=\"41\" y2=\"4\" />\n",
-       "  <line x1=\"18\" y1=\"8\" x2=\"45\" y2=\"8\" />\n",
-       "  <line x1=\"23\" y1=\"13\" x2=\"50\" y2=\"13\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"42\" y2=\"5\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"48\" y2=\"11\" />\n",
        "  <line x1=\"27\" y1=\"17\" x2=\"54\" y2=\"17\" />\n",
-       "  <line x1=\"32\" y1=\"22\" x2=\"58\" y2=\"22\" />\n",
-       "  <line x1=\"36\" y1=\"26\" x2=\"63\" y2=\"26\" />\n",
-       "  <line x1=\"40\" y1=\"30\" x2=\"67\" y2=\"30\" />\n",
-       "  <line x1=\"45\" y1=\"35\" x2=\"72\" y2=\"35\" />\n",
-       "  <line x1=\"49\" y1=\"39\" x2=\"76\" y2=\"39\" />\n",
-       "  <line x1=\"54\" y1=\"44\" x2=\"80\" y2=\"44\" />\n",
-       "  <line x1=\"58\" y1=\"48\" x2=\"85\" y2=\"48\" />\n",
+       "  <line x1=\"33\" y1=\"23\" x2=\"60\" y2=\"23\" />\n",
+       "  <line x1=\"39\" y1=\"29\" x2=\"65\" y2=\"29\" />\n",
+       "  <line x1=\"44\" y1=\"34\" x2=\"71\" y2=\"34\" />\n",
+       "  <line x1=\"50\" y1=\"40\" x2=\"77\" y2=\"40\" />\n",
+       "  <line x1=\"56\" y1=\"46\" x2=\"83\" y2=\"46\" />\n",
        "  <line x1=\"62\" y1=\"52\" x2=\"89\" y2=\"52\" />\n",
-       "  <line x1=\"67\" y1=\"57\" x2=\"94\" y2=\"57\" />\n",
-       "  <line x1=\"71\" y1=\"61\" x2=\"98\" y2=\"61\" />\n",
-       "  <line x1=\"76\" y1=\"66\" x2=\"102\" y2=\"66\" />\n",
+       "  <line x1=\"68\" y1=\"58\" x2=\"94\" y2=\"58\" />\n",
+       "  <line x1=\"74\" y1=\"64\" x2=\"100\" y2=\"64\" />\n",
+       "  <line x1=\"79\" y1=\"69\" x2=\"106\" y2=\"69\" />\n",
        "  <line x1=\"80\" y1=\"70\" x2=\"107\" y2=\"70\" style=\"stroke-width:2\" />\n",
        "\n",
        "  <!-- Vertical lines -->\n",
@@ -4193,14 +4388,42 @@
        "</svg>\n",
        "        </td>\n",
        "    </tr>\n",
-       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2010-01-01T01:30:00 ... 2015-01-...</div><input id='attrs-5dda3fc7-a4ae-4e8b-8d2f-cc0dbd38e15b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5dda3fc7-a4ae-4e8b-8d2f-cc0dbd38e15b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f47111aa-118d-4591-8e04-fbd2aaef0e3b' class='xr-var-data-in' type='checkbox'><label for='data-f47111aa-118d-4591-8e04-fbd2aaef0e3b' 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>xcdat_bounds :</span></dt><dd>True</dd></dl></div><div class='xr-var-data'><pre>array([[&#x27;2010-01-01T01:30:00.000000000&#x27;, &#x27;2010-01-01T04:30:00.000000000&#x27;],\n",
-       "       [&#x27;2010-01-01T04:30:00.000000000&#x27;, &#x27;2010-01-01T07:30:00.000000000&#x27;],\n",
-       "       [&#x27;2010-01-01T07:30:00.000000000&#x27;, &#x27;2010-01-01T10:30:00.000000000&#x27;],\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>2010-01-01 03:00:00 ... 2015-01-...</div><input id='attrs-6942012d-01a1-4491-809e-0e8614c4daf8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6942012d-01a1-4491-809e-0e8614c4daf8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f836f812-e163-4a68-9413-305420060ef8' class='xr-var-data-in' type='checkbox'><label for='data-f836f812-e163-4a68-9413-305420060ef8' 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>xcdat_bounds :</span></dt><dd>True</dd></dl></div><div class='xr-var-data'><pre>array([[cftime.DatetimeProlepticGregorian(2010, 1, 1, 3, 0, 0, 0, has_year_zero=True),\n",
+       "        cftime.DatetimeProlepticGregorian(2010, 1, 1, 6, 0, 0, 0, has_year_zero=True)],\n",
+       "       [cftime.DatetimeProlepticGregorian(2010, 1, 1, 6, 0, 0, 0, has_year_zero=True),\n",
+       "        cftime.DatetimeProlepticGregorian(2010, 1, 1, 9, 0, 0, 0, has_year_zero=True)],\n",
+       "       [cftime.DatetimeProlepticGregorian(2010, 1, 1, 9, 0, 0, 0, has_year_zero=True),\n",
+       "        cftime.DatetimeProlepticGregorian(2010, 1, 1, 12, 0, 0, 0, has_year_zero=True)],\n",
        "       ...,\n",
-       "       [&#x27;2014-12-31T16:30:00.000000000&#x27;, &#x27;2014-12-31T19:30:00.000000000&#x27;],\n",
-       "       [&#x27;2014-12-31T19:30:00.000000000&#x27;, &#x27;2014-12-31T22:30:00.000000000&#x27;],\n",
-       "       [&#x27;2014-12-31T22:30:00.000000000&#x27;, &#x27;2015-01-01T01:30:00.000000000&#x27;]],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-147dbd4b-8a2b-4f90-b25e-b60aff5bcf69' class='xr-section-summary-in' type='checkbox'  ><label for='section-147dbd4b-8a2b-4f90-b25e-b60aff5bcf69' class='xr-section-summary' >Attributes: <span>(48)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>0.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>87658.0</dd><dt><span>creation_date :</span></dt><dd>2020-06-05T04:54:56Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.30</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>3hrPt</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.CSIRO.ACCESS-ESM1-5.historical.none.r10i1p1f1</dd><dt><span>grid :</span></dt><dd>native atmosphere N96 grid (145x192 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>history :</span></dt><dd>2020-06-05T04:54:56Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 CMIP-6.2 and CF standards.</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia</dd><dt><span>institution_id :</span></dt><dd>CSIRO</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>nominal_resolution :</span></dt><dd>250 km</dd><dt><span>notes :</span></dt><dd>Exp: ESM-historical; Local ID: HI-14; Variable: tas ([&#x27;fld_s03i236&#x27;])</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>ACCESS-ESM1-5</dd><dt><span>parent_time_units :</span></dt><dd>days since 0101-1-1</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>10</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>run_variant :</span></dt><dd>forcing: GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4, CFC11, CFC12, CFC113, HCFC22, HFC125, HFC134a)</dd><dt><span>source :</span></dt><dd>ACCESS-ESM1.5 (2019): \n",
+       "       [cftime.DatetimeProlepticGregorian(2014, 12, 31, 18, 0, 0, 0, has_year_zero=True),\n",
+       "        cftime.DatetimeProlepticGregorian(2014, 12, 31, 21, 0, 0, 0, has_year_zero=True)],\n",
+       "       [cftime.DatetimeProlepticGregorian(2014, 12, 31, 21, 0, 0, 0, has_year_zero=True),\n",
+       "        cftime.DatetimeProlepticGregorian(2015, 1, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
+       "       [cftime.DatetimeProlepticGregorian(2015, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
+       "        cftime.DatetimeProlepticGregorian(2015, 1, 1, 3, 0, 0, 0, has_year_zero=True)]],\n",
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8b1b2c03-d3ee-4d88-9fec-fdfe9974cc4c' class='xr-section-summary-in' type='checkbox'  ><label for='section-8b1b2c03-d3ee-4d88-9fec-fdfe9974cc4c' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-19d8f8b2-8678-4642-a676-2d030b1fac15' class='xr-index-data-in' type='checkbox'/><label for='index-19d8f8b2-8678-4642-a676-2d030b1fac15' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -90.0, -88.75,  -87.5, -86.25,  -85.0, -83.75,  -82.5, -81.25,  -80.0,\n",
+       "       -78.75,\n",
+       "       ...\n",
+       "        78.75,   80.0,  81.25,   82.5,  83.75,   85.0,  86.25,   87.5,  88.75,\n",
+       "         90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=145))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-359ebd15-4a33-4039-96b5-8a058aa97dc4' class='xr-index-data-in' type='checkbox'/><label for='index-359ebd15-4a33-4039-96b5-8a058aa97dc4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([    0.0,   1.875,    3.75,   5.625,     7.5,   9.375,   11.25,  13.125,\n",
+       "          15.0,  16.875,\n",
+       "       ...\n",
+       "        341.25, 343.125,   345.0, 346.875,  348.75, 350.625,   352.5, 354.375,\n",
+       "        356.25, 358.125],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3fdc1b66-5bcd-4ee5-882f-79fc6a3a5fb5' class='xr-index-data-in' type='checkbox'/><label for='index-3fdc1b66-5bcd-4ee5-882f-79fc6a3a5fb5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([2010-01-01 03:00:00, 2010-01-01 06:00:00, 2010-01-01 09:00:00,\n",
+       "             2010-01-01 12:00:00, 2010-01-01 15:00:00, 2010-01-01 18:00:00,\n",
+       "             2010-01-01 21:00:00, 2010-01-02 00:00:00, 2010-01-02 03:00:00,\n",
+       "             2010-01-02 06:00:00,\n",
+       "             ...\n",
+       "             2014-12-30 21:00:00, 2014-12-31 00:00:00, 2014-12-31 03:00:00,\n",
+       "             2014-12-31 06:00:00, 2014-12-31 09:00:00, 2014-12-31 12:00:00,\n",
+       "             2014-12-31 15:00:00, 2014-12-31 18:00:00, 2014-12-31 21:00:00,\n",
+       "             2015-01-01 00:00:00],\n",
+       "            dtype=&#x27;object&#x27;,\n",
+       "            length=14608,\n",
+       "            calendar=&#x27;proleptic_gregorian&#x27;,\n",
+       "            freq=&#x27;3h&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f629a43d-8869-42df-adb6-1edd4c1e9723' class='xr-section-summary-in' type='checkbox'  ><label for='section-f629a43d-8869-42df-adb6-1edd4c1e9723' class='xr-section-summary' >Attributes: <span>(48)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>0.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>87658.0</dd><dt><span>creation_date :</span></dt><dd>2020-06-05T04:54:56Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.30</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>3hrPt</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.CSIRO.ACCESS-ESM1-5.historical.none.r10i1p1f1</dd><dt><span>grid :</span></dt><dd>native atmosphere N96 grid (145x192 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>history :</span></dt><dd>2020-06-05T04:54:56Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 CMIP-6.2 and CF standards.</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia</dd><dt><span>institution_id :</span></dt><dd>CSIRO</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>nominal_resolution :</span></dt><dd>250 km</dd><dt><span>notes :</span></dt><dd>Exp: ESM-historical; Local ID: HI-14; Variable: tas ([&#x27;fld_s03i236&#x27;])</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>ACCESS-ESM1-5</dd><dt><span>parent_time_units :</span></dt><dd>days since 0101-1-1</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>10</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>run_variant :</span></dt><dd>forcing: GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4, CFC11, CFC12, CFC113, HCFC22, HFC125, HFC134a)</dd><dt><span>source :</span></dt><dd>ACCESS-ESM1.5 (2019): \n",
        "aerosol: CLASSIC (v1.0)\n",
        "atmos: HadGAM2 (r1.1, N96; 192 x 145 longitude/latitude; 38 levels; top level 39255 m)\n",
        "atmosChem: none\n",
@@ -4211,19 +4434,19 @@
        "seaIce: CICE4.1 (same grid as ocean)</dd><dt><span>source_id :</span></dt><dd>ACCESS-ESM1-5</dd><dt><span>source_type :</span></dt><dd>AOGCM</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>3hr</dd><dt><span>table_info :</span></dt><dd>Creation Date:(30 April 2019) MD5:5bd755e94c2173cb3050a0f3480f60c4</dd><dt><span>title :</span></dt><dd>ACCESS-ESM1-5 output prepared for CMIP6</dd><dt><span>variable_id :</span></dt><dd>tas</dd><dt><span>variant_label :</span></dt><dd>r10i1p1f1</dd><dt><span>version :</span></dt><dd>v20200605</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by CSIRO is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment.  Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file). The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.4.0</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/b79e6a05-c482-46cf-b3b8-83b9a7d0cfdd</dd><dt><span>DODS_EXTRA.Unlimited_Dimension :</span></dt><dd>time</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
-       "<xarray.Dataset>\n",
-       "Dimensions:    (time: 14608, lat: 145, bnds: 2, lon: 192)\n",
+       "<xarray.Dataset> Size: 2GB\n",
+       "Dimensions:    (lat: 145, bnds: 2, lon: 192, time: 14608)\n",
        "Coordinates:\n",
-       "  * time       (time) datetime64[ns] 2010-01-01T03:00:00 ... 2015-01-01\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 ... 352.5 354.4 356.2 358.1\n",
-       "    height     float64 ...\n",
+       "  * lat        (lat) float64 1kB -90.0 -88.75 -87.5 -86.25 ... 87.5 88.75 90.0\n",
+       "  * lon        (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 354.4 356.2 358.1\n",
+       "    height     float64 8B ...\n",
+       "  * time       (time) object 117kB 2010-01-01 03:00:00 ... 2015-01-01 00:00:00\n",
        "Dimensions without coordinates: bnds\n",
        "Data variables:\n",
-       "    lat_bnds   (lat, bnds) float64 dask.array<chunksize=(145, 2), meta=np.ndarray>\n",
-       "    lon_bnds   (lon, bnds) float64 dask.array<chunksize=(192, 2), meta=np.ndarray>\n",
-       "    tas        (time, lat, lon) float32 dask.array<chunksize=(913, 145, 192), meta=np.ndarray>\n",
-       "    time_bnds  (time, bnds) datetime64[ns] 2010-01-01T01:30:00 ... 2015-01-01...\n",
+       "    lat_bnds   (lat, bnds) float64 2kB dask.array<chunksize=(145, 2), meta=np.ndarray>\n",
+       "    lon_bnds   (lon, bnds) float64 3kB dask.array<chunksize=(192, 2), meta=np.ndarray>\n",
+       "    tas        (time, lat, lon) float32 2GB dask.array<chunksize=(1205, 145, 192), meta=np.ndarray>\n",
+       "    time_bnds  (time, bnds) object 234kB 2010-01-01 03:00:00 ... 2015-01-01 0...\n",
        "Attributes: (12/48)\n",
        "    Conventions:                     CF-1.7 CMIP-6.2\n",
        "    activity_id:                     CMIP\n",
@@ -4240,7 +4463,7 @@
        "    DODS_EXTRA.Unlimited_Dimension:  time"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4252,6 +4475,7 @@
     "ds2 = xcdat.open_dataset(\n",
     "    \"https://esgf-data1.llnl.gov/thredds/dodsC/css03_data/CMIP6/CMIP/CSIRO/ACCESS-ESM1-5/historical/r10i1p1f1/3hr/tas/gn/v20200605/tas_3hr_ACCESS-ESM1-5_historical_r10i1p1f1_gn_201001010300-201501010000.nc\",\n",
     "    chunks={\"time\": \"auto\"},\n",
+    "    add_bounds=[\"T\"],\n",
     ")\n",
     "\n",
     "# Unit adjust (-273.15, K to C)\n",
@@ -4262,7 +4486,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4271,7 +4495,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -4538,6 +4762,11 @@
        "  grid-column: 4;\n",
        "}\n",
        "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
        ".xr-var-name,\n",
        ".xr-var-dims,\n",
        ".xr-var-dtype,\n",
@@ -4559,14 +4788,16 @@
        "}\n",
        "\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-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",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
        "  display: block;\n",
        "}\n",
        "\n",
@@ -4576,13 +4807,16 @@
        "\n",
        ".xr-var-name span,\n",
        ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
        ".xr-attrs {\n",
        "  padding-left: 25px !important;\n",
        "}\n",
        "\n",
        ".xr-attrs,\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
        "  grid-column: 1 / -1;\n",
        "}\n",
        "\n",
@@ -4620,7 +4854,8 @@
        "}\n",
        "\n",
        ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
        "  display: inline-block;\n",
        "  vertical-align: middle;\n",
        "  width: 1em;\n",
@@ -4629,21 +4864,21 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tas&#x27; (time: 61, lat: 145, lon: 192)&gt;\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tas&#x27; (time: 61, lat: 145, lon: 192)&gt; Size: 14MB\n",
        "dask.array&lt;truediv, shape=(61, 145, 192), dtype=float64, chunksize=(1, 145, 192), chunktype=numpy.ndarray&gt;\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",
-       "    height   float64 ...\n",
-       "  * time     (time) object 2010-01-01 00:00:00 ... 2015-01-01 00:00:00\n",
+       "  * lat      (lat) float64 1kB -90.0 -88.75 -87.5 -86.25 ... 87.5 88.75 90.0\n",
+       "  * lon      (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 352.5 354.4 356.2 358.1\n",
+       "    height   float64 8B ...\n",
+       "  * time     (time) object 488B 2010-01-01 00:00:00 ... 2015-01-01 00:00:00\n",
        "Attributes:\n",
        "    operation:  temporal_avg\n",
        "    mode:       group_average\n",
        "    freq:       month\n",
-       "    weighted:   True</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'tas'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 61</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-d00a4dc5-0ff7-460b-ae8f-bf6d12422a20' class='xr-array-in' type='checkbox' checked><label for='section-d00a4dc5-0ff7-460b-ae8f-bf6d12422a20' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 145, 192), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    weighted:   True</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'tas'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 61</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-f4dba92c-65e3-42f6-834c-8638ff3d802e' class='xr-array-in' type='checkbox' checked><label for='section-f4dba92c-65e3-42f6-834c-8638ff3d802e' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 145, 192), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
        "    <tr>\n",
        "        <td>\n",
-       "            <table>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
        "                <thead>\n",
        "                    <tr>\n",
        "                        <td> </td>\n",
@@ -4665,14 +4900,12 @@
        "                        <td> (1, 145, 192) </td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
-       "                        <th> Count </th>\n",
-       "                        <td> 623 Graph Layers </td>\n",
-       "                        <td> 61 Chunks </td>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 61 chunks in 641 graph layers </td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
-       "                    <th> Type </th>\n",
-       "                    <td> float64 </td>\n",
-       "                    <td> numpy.ndarray </td>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
        "                    </tr>\n",
        "                </tbody>\n",
        "            </table>\n",
@@ -4756,7 +4989,7 @@
        "</svg>\n",
        "        </td>\n",
        "    </tr>\n",
-       "</table></div></div></li><li class='xr-section-item'><input id='section-5034d4ae-5af9-4910-9acb-e71fc60b3822' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5034d4ae-5af9-4910-9acb-e71fc60b3822' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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-2e8c313f-e6fa-414a-ad7f-8fbacf1a8929' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2e8c313f-e6fa-414a-ad7f-8fbacf1a8929' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63c05a40-b638-4735-9811-bf5eada27ef3' class='xr-var-data-in' type='checkbox'><label for='data-63c05a40-b638-4735-9811-bf5eada27ef3' 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",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-4a57feb5-26c9-4347-991e-26dfaa4f9c41' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4a57feb5-26c9-4347-991e-26dfaa4f9c41' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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-3b15297e-3383-48d5-900e-721d56e550c3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b15297e-3383-48d5-900e-721d56e550c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78822c5d-5137-40d3-a35c-ad2c3d7d998d' class='xr-var-data-in' type='checkbox'><label for='data-78822c5d-5137-40d3-a35c-ad2c3d7d998d' 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",
@@ -4772,7 +5005,7 @@
        "        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-509d81e6-6983-4cce-8f76-ba61baa9c52c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-509d81e6-6983-4cce-8f76-ba61baa9c52c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1278952d-7e49-4063-b9e7-27a13b113b4c' class='xr-var-data-in' type='checkbox'><label for='data-1278952d-7e49-4063-b9e7-27a13b113b4c' 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",
+       "        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-d4f250ee-06d6-4773-8311-916e1037b787' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d4f250ee-06d6-4773-8311-916e1037b787' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9661358c-1d28-4293-ae08-6a76d836c124' class='xr-var-data-in' type='checkbox'><label for='data-9661358c-1d28-4293-ae08-6a76d836c124' 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",
@@ -4795,7 +5028,7 @@
        "       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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cf69e630-deca-40e6-a50a-27638ae01dcc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cf69e630-deca-40e6-a50a-27638ae01dcc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f967eca3-4177-4b16-9e4a-1763ff8ab25d' class='xr-var-data-in' type='checkbox'><label for='data-f967eca3-4177-4b16-9e4a-1763ff8ab25d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</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'>object</div><div class='xr-var-preview xr-preview'>2010-01-01 00:00:00 ... 2015-01-...</div><input id='attrs-fc462871-72c0-4a98-b0c4-604347e4b9fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fc462871-72c0-4a98-b0c4-604347e4b9fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1af1bbc1-70ba-4a68-95ac-3261ed41c615' class='xr-var-data-in' type='checkbox'><label for='data-1af1bbc1-70ba-4a68-95ac-3261ed41c615' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeProlepticGregorian(2010, 1, 1, 0, 0, 0, 0, has_year_zero=True),\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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-76cd5c9f-3fe0-4d51-9586-343ffc08dd2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-76cd5c9f-3fe0-4d51-9586-343ffc08dd2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5cefe20-09c5-4e0c-9f95-97efb2dcbfe6' class='xr-var-data-in' type='checkbox'><label for='data-b5cefe20-09c5-4e0c-9f95-97efb2dcbfe6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><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'>2010-01-01 00:00:00 ... 2015-01-...</div><input id='attrs-59f9013e-77ee-46c9-b82c-e1426dafb051' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59f9013e-77ee-46c9-b82c-e1426dafb051' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a616374d-72e7-446c-b81f-f7aaacfb7d30' class='xr-var-data-in' type='checkbox'><label for='data-a616374d-72e7-446c-b81f-f7aaacfb7d30' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeProlepticGregorian(2010, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(2010, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(2010, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(2010, 4, 1, 0, 0, 0, 0, has_year_zero=True),\n",
@@ -4856,16 +5089,50 @@
        "       cftime.DatetimeProlepticGregorian(2014, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(2014, 12, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(2015, 1, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
-       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-498fdaa8-6ea4-47ee-b02a-91ed265015fb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-498fdaa8-6ea4-47ee-b02a-91ed265015fb' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><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>month</dd><dt><span>weighted :</span></dt><dd>True</dd></dl></div></li></ul></div></div>"
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7ddf8d25-82b6-48c8-88d7-ebef2a9ba80c' class='xr-section-summary-in' type='checkbox'  ><label for='section-7ddf8d25-82b6-48c8-88d7-ebef2a9ba80c' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-23fb81a4-292b-4159-aa6e-d224060976cf' class='xr-index-data-in' type='checkbox'/><label for='index-23fb81a4-292b-4159-aa6e-d224060976cf' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -90.0, -88.75,  -87.5, -86.25,  -85.0, -83.75,  -82.5, -81.25,  -80.0,\n",
+       "       -78.75,\n",
+       "       ...\n",
+       "        78.75,   80.0,  81.25,   82.5,  83.75,   85.0,  86.25,   87.5,  88.75,\n",
+       "         90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=145))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c67d0c15-26ae-40af-baf3-8d29d4eefae4' class='xr-index-data-in' type='checkbox'/><label for='index-c67d0c15-26ae-40af-baf3-8d29d4eefae4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([    0.0,   1.875,    3.75,   5.625,     7.5,   9.375,   11.25,  13.125,\n",
+       "          15.0,  16.875,\n",
+       "       ...\n",
+       "        341.25, 343.125,   345.0, 346.875,  348.75, 350.625,   352.5, 354.375,\n",
+       "        356.25, 358.125],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c1b4a1ac-5b56-4efe-bf07-e395853b3f75' class='xr-index-data-in' type='checkbox'/><label for='index-c1b4a1ac-5b56-4efe-bf07-e395853b3f75' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([2010-01-01 00:00:00, 2010-02-01 00:00:00, 2010-03-01 00:00:00,\n",
+       "             2010-04-01 00:00:00, 2010-05-01 00:00:00, 2010-06-01 00:00:00,\n",
+       "             2010-07-01 00:00:00, 2010-08-01 00:00:00, 2010-09-01 00:00:00,\n",
+       "             2010-10-01 00:00:00, 2010-11-01 00:00:00, 2010-12-01 00:00:00,\n",
+       "             2011-01-01 00:00:00, 2011-02-01 00:00:00, 2011-03-01 00:00:00,\n",
+       "             2011-04-01 00:00:00, 2011-05-01 00:00:00, 2011-06-01 00:00:00,\n",
+       "             2011-07-01 00:00:00, 2011-08-01 00:00:00, 2011-09-01 00:00:00,\n",
+       "             2011-10-01 00:00:00, 2011-11-01 00:00:00, 2011-12-01 00:00:00,\n",
+       "             2012-01-01 00:00:00, 2012-02-01 00:00:00, 2012-03-01 00:00:00,\n",
+       "             2012-04-01 00:00:00, 2012-05-01 00:00:00, 2012-06-01 00:00:00,\n",
+       "             2012-07-01 00:00:00, 2012-08-01 00:00:00, 2012-09-01 00:00:00,\n",
+       "             2012-10-01 00:00:00, 2012-11-01 00:00:00, 2012-12-01 00:00:00,\n",
+       "             2013-01-01 00:00:00, 2013-02-01 00:00:00, 2013-03-01 00:00:00,\n",
+       "             2013-04-01 00:00:00, 2013-05-01 00:00:00, 2013-06-01 00:00:00,\n",
+       "             2013-07-01 00:00:00, 2013-08-01 00:00:00, 2013-09-01 00:00:00,\n",
+       "             2013-10-01 00:00:00, 2013-11-01 00:00:00, 2013-12-01 00:00:00,\n",
+       "             2014-01-01 00:00:00, 2014-02-01 00:00:00, 2014-03-01 00:00:00,\n",
+       "             2014-04-01 00:00:00, 2014-05-01 00:00:00, 2014-06-01 00:00:00,\n",
+       "             2014-07-01 00:00:00, 2014-08-01 00:00:00, 2014-09-01 00:00:00,\n",
+       "             2014-10-01 00:00:00, 2014-11-01 00:00:00, 2014-12-01 00:00:00,\n",
+       "             2015-01-01 00:00:00],\n",
+       "            dtype=&#x27;object&#x27;,\n",
+       "            length=61,\n",
+       "            calendar=&#x27;proleptic_gregorian&#x27;,\n",
+       "            freq=&#x27;MS&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a143c565-98ee-4ddb-bb50-e8d336234dbd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a143c565-98ee-4ddb-bb50-e8d336234dbd' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><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>month</dd><dt><span>weighted :</span></dt><dd>True</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
-       "<xarray.DataArray 'tas' (time: 61, lat: 145, lon: 192)>\n",
+       "<xarray.DataArray 'tas' (time: 61, lat: 145, lon: 192)> Size: 14MB\n",
        "dask.array<truediv, shape=(61, 145, 192), dtype=float64, chunksize=(1, 145, 192), chunktype=numpy.ndarray>\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",
-       "    height   float64 ...\n",
-       "  * time     (time) object 2010-01-01 00:00:00 ... 2015-01-01 00:00:00\n",
+       "  * lat      (lat) float64 1kB -90.0 -88.75 -87.5 -86.25 ... 87.5 88.75 90.0\n",
+       "  * lon      (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 352.5 354.4 356.2 358.1\n",
+       "    height   float64 8B ...\n",
+       "  * time     (time) object 488B 2010-01-01 00:00:00 ... 2015-01-01 00:00:00\n",
        "Attributes:\n",
        "    operation:  temporal_avg\n",
        "    mode:       group_average\n",
@@ -4873,7 +5140,7 @@
        "    weighted:   True"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4895,7 +5162,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4905,6 +5172,7 @@
     "ds3 = xcdat.open_dataset(\n",
     "    \"https://esgf-data1.llnl.gov/thredds/dodsC/css03_data/CMIP6/CMIP/CSIRO/ACCESS-ESM1-5/historical/r10i1p1f1/3hr/tas/gn/v20200605/tas_3hr_ACCESS-ESM1-5_historical_r10i1p1f1_gn_201001010300-201501010000.nc\",\n",
     "    chunks={\"time\": \"auto\"},\n",
+    "    add_bounds=[\"T\"],\n",
     ")\n",
     "\n",
     "# Unit adjust (-273.15, K to C)\n",
@@ -4913,7 +5181,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -5180,6 +5448,11 @@
        "  grid-column: 4;\n",
        "}\n",
        "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
        ".xr-var-name,\n",
        ".xr-var-dims,\n",
        ".xr-var-dtype,\n",
@@ -5201,14 +5474,16 @@
        "}\n",
        "\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-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",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
        "  display: block;\n",
        "}\n",
        "\n",
@@ -5218,13 +5493,16 @@
        "\n",
        ".xr-var-name span,\n",
        ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
        ".xr-attrs {\n",
        "  padding-left: 25px !important;\n",
        "}\n",
        "\n",
        ".xr-attrs,\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
        "  grid-column: 1 / -1;\n",
        "}\n",
        "\n",
@@ -5262,7 +5540,8 @@
        "}\n",
        "\n",
        ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
        "  display: inline-block;\n",
        "  vertical-align: middle;\n",
        "  width: 1em;\n",
@@ -5271,16 +5550,16 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tas&#x27; (time: 14608, lat: 145, lon: 192)&gt;\n",
-       "dask.array&lt;sub, shape=(14608, 145, 192), dtype=float32, chunksize=(913, 145, 192), chunktype=numpy.ndarray&gt;\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tas&#x27; (time: 14608, lat: 145, lon: 192)&gt; Size: 2GB\n",
+       "dask.array&lt;sub, shape=(14608, 145, 192), dtype=float32, chunksize=(1205, 145, 192), chunktype=numpy.ndarray&gt;\n",
        "Coordinates:\n",
-       "  * time     (time) datetime64[ns] 2010-01-01T03:00:00 ... 2015-01-01\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",
-       "    height   float64 ...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'tas'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 14608</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-6b1d6a6d-7188-44b9-85f6-93216c38fdce' class='xr-array-in' type='checkbox' checked><label for='section-6b1d6a6d-7188-44b9-85f6-93216c38fdce' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(913, 145, 192), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "  * lat      (lat) float64 1kB -90.0 -88.75 -87.5 -86.25 ... 87.5 88.75 90.0\n",
+       "  * lon      (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 352.5 354.4 356.2 358.1\n",
+       "    height   float64 8B ...\n",
+       "  * time     (time) object 117kB 2010-01-01 03:00:00 ... 2015-01-01 00:00:00</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'>'tas'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 14608</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-32734076-2f7d-49e1-ab50-e1a2c9ada802' class='xr-array-in' type='checkbox' checked><label for='section-32734076-2f7d-49e1-ab50-e1a2c9ada802' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1205, 145, 192), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
        "    <tr>\n",
        "        <td>\n",
-       "            <table>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
        "                <thead>\n",
        "                    <tr>\n",
        "                        <td> </td>\n",
@@ -5293,23 +5572,21 @@
        "                    <tr>\n",
        "                        <th> Bytes </th>\n",
        "                        <td> 1.52 GiB </td>\n",
-       "                        <td> 96.96 MiB </td>\n",
+       "                        <td> 127.97 MiB </td>\n",
        "                    </tr>\n",
        "                    \n",
        "                    <tr>\n",
        "                        <th> Shape </th>\n",
        "                        <td> (14608, 145, 192) </td>\n",
-       "                        <td> (913, 145, 192) </td>\n",
+       "                        <td> (1205, 145, 192) </td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
-       "                        <th> Count </th>\n",
-       "                        <td> 3 Graph Layers </td>\n",
-       "                        <td> 16 Chunks </td>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 13 chunks in 3 graph layers </td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
-       "                    <th> Type </th>\n",
-       "                    <td> float32 </td>\n",
-       "                    <td> numpy.ndarray </td>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
        "                    </tr>\n",
        "                </tbody>\n",
        "            </table>\n",
@@ -5323,21 +5600,18 @@
        "\n",
        "  <!-- Vertical lines -->\n",
        "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"25\" style=\"stroke-width:2\" />\n",
-       "  <line x1=\"14\" y1=\"4\" x2=\"14\" y2=\"29\" />\n",
-       "  <line x1=\"18\" y1=\"8\" x2=\"18\" y2=\"34\" />\n",
-       "  <line x1=\"23\" y1=\"13\" x2=\"23\" y2=\"38\" />\n",
-       "  <line x1=\"27\" y1=\"17\" x2=\"27\" y2=\"43\" />\n",
-       "  <line x1=\"32\" y1=\"22\" x2=\"32\" y2=\"47\" />\n",
-       "  <line x1=\"36\" y1=\"26\" x2=\"36\" y2=\"51\" />\n",
-       "  <line x1=\"40\" y1=\"30\" x2=\"40\" y2=\"56\" />\n",
-       "  <line x1=\"45\" y1=\"35\" x2=\"45\" y2=\"60\" />\n",
-       "  <line x1=\"49\" y1=\"39\" x2=\"49\" y2=\"65\" />\n",
-       "  <line x1=\"54\" y1=\"44\" x2=\"54\" y2=\"69\" />\n",
-       "  <line x1=\"58\" y1=\"48\" x2=\"58\" y2=\"73\" />\n",
-       "  <line x1=\"62\" y1=\"52\" x2=\"62\" y2=\"78\" />\n",
-       "  <line x1=\"67\" y1=\"57\" x2=\"67\" y2=\"82\" />\n",
-       "  <line x1=\"71\" y1=\"61\" x2=\"71\" y2=\"87\" />\n",
-       "  <line x1=\"76\" y1=\"66\" x2=\"76\" y2=\"91\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"15\" y2=\"31\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"21\" y2=\"37\" />\n",
+       "  <line x1=\"27\" y1=\"17\" x2=\"27\" y2=\"42\" />\n",
+       "  <line x1=\"33\" y1=\"23\" x2=\"33\" y2=\"48\" />\n",
+       "  <line x1=\"39\" y1=\"29\" x2=\"39\" y2=\"54\" />\n",
+       "  <line x1=\"44\" y1=\"34\" x2=\"44\" y2=\"60\" />\n",
+       "  <line x1=\"50\" y1=\"40\" x2=\"50\" y2=\"66\" />\n",
+       "  <line x1=\"56\" y1=\"46\" x2=\"56\" y2=\"71\" />\n",
+       "  <line x1=\"62\" y1=\"52\" x2=\"62\" y2=\"77\" />\n",
+       "  <line x1=\"68\" y1=\"58\" x2=\"68\" y2=\"83\" />\n",
+       "  <line x1=\"74\" y1=\"64\" x2=\"74\" y2=\"89\" />\n",
+       "  <line x1=\"79\" y1=\"69\" x2=\"79\" y2=\"95\" />\n",
        "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"96\" style=\"stroke-width:2\" />\n",
        "\n",
        "  <!-- Colored Rectangle -->\n",
@@ -5345,21 +5619,18 @@
        "\n",
        "  <!-- Horizontal lines -->\n",
        "  <line x1=\"10\" y1=\"0\" x2=\"36\" y2=\"0\" style=\"stroke-width:2\" />\n",
-       "  <line x1=\"14\" y1=\"4\" x2=\"41\" y2=\"4\" />\n",
-       "  <line x1=\"18\" y1=\"8\" x2=\"45\" y2=\"8\" />\n",
-       "  <line x1=\"23\" y1=\"13\" x2=\"50\" y2=\"13\" />\n",
+       "  <line x1=\"15\" y1=\"5\" x2=\"42\" y2=\"5\" />\n",
+       "  <line x1=\"21\" y1=\"11\" x2=\"48\" y2=\"11\" />\n",
        "  <line x1=\"27\" y1=\"17\" x2=\"54\" y2=\"17\" />\n",
-       "  <line x1=\"32\" y1=\"22\" x2=\"58\" y2=\"22\" />\n",
-       "  <line x1=\"36\" y1=\"26\" x2=\"63\" y2=\"26\" />\n",
-       "  <line x1=\"40\" y1=\"30\" x2=\"67\" y2=\"30\" />\n",
-       "  <line x1=\"45\" y1=\"35\" x2=\"72\" y2=\"35\" />\n",
-       "  <line x1=\"49\" y1=\"39\" x2=\"76\" y2=\"39\" />\n",
-       "  <line x1=\"54\" y1=\"44\" x2=\"80\" y2=\"44\" />\n",
-       "  <line x1=\"58\" y1=\"48\" x2=\"85\" y2=\"48\" />\n",
+       "  <line x1=\"33\" y1=\"23\" x2=\"60\" y2=\"23\" />\n",
+       "  <line x1=\"39\" y1=\"29\" x2=\"65\" y2=\"29\" />\n",
+       "  <line x1=\"44\" y1=\"34\" x2=\"71\" y2=\"34\" />\n",
+       "  <line x1=\"50\" y1=\"40\" x2=\"77\" y2=\"40\" />\n",
+       "  <line x1=\"56\" y1=\"46\" x2=\"83\" y2=\"46\" />\n",
        "  <line x1=\"62\" y1=\"52\" x2=\"89\" y2=\"52\" />\n",
-       "  <line x1=\"67\" y1=\"57\" x2=\"94\" y2=\"57\" />\n",
-       "  <line x1=\"71\" y1=\"61\" x2=\"98\" y2=\"61\" />\n",
-       "  <line x1=\"76\" y1=\"66\" x2=\"102\" y2=\"66\" />\n",
+       "  <line x1=\"68\" y1=\"58\" x2=\"94\" y2=\"58\" />\n",
+       "  <line x1=\"74\" y1=\"64\" x2=\"100\" y2=\"64\" />\n",
+       "  <line x1=\"79\" y1=\"69\" x2=\"106\" y2=\"69\" />\n",
        "  <line x1=\"80\" y1=\"70\" x2=\"107\" y2=\"70\" style=\"stroke-width:2\" />\n",
        "\n",
        "  <!-- Vertical lines -->\n",
@@ -5387,10 +5658,7 @@
        "</svg>\n",
        "        </td>\n",
        "    </tr>\n",
-       "</table></div></div></li><li class='xr-section-item'><input id='section-4a94ad0b-49bb-4f95-bf84-dc24118ffff8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4a94ad0b-49bb-4f95-bf84-dc24118ffff8' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2010-01-01T03:00:00 ... 2015-01-01</div><input id='attrs-06ac9c90-a1de-428b-bc0a-360e30744cb6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06ac9c90-a1de-428b-bc0a-360e30744cb6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2fe032a6-cb96-4101-b29c-3f86bbb89b13' class='xr-var-data-in' type='checkbox'><label for='data-2fe032a6-cb96-4101-b29c-3f86bbb89b13' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2010-01-01T03:00:00.000000000&#x27;, &#x27;2010-01-01T06:00:00.000000000&#x27;,\n",
-       "       &#x27;2010-01-01T09:00:00.000000000&#x27;, ..., &#x27;2014-12-31T18:00:00.000000000&#x27;,\n",
-       "       &#x27;2014-12-31T21:00:00.000000000&#x27;, &#x27;2015-01-01T00:00:00.000000000&#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-03b39bb8-2a81-4377-82ca-674f08b91ad7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-03b39bb8-2a81-4377-82ca-674f08b91ad7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce6f65c0-db69-4082-afe4-dac28d5b10e9' class='xr-var-data-in' type='checkbox'><label for='data-ce6f65c0-db69-4082-afe4-dac28d5b10e9' 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",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-d9f134e9-d487-4d11-b506-dba454dda01b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d9f134e9-d487-4d11-b506-dba454dda01b' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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-e7a21441-2576-4fcf-8e40-02019f020cb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7a21441-2576-4fcf-8e40-02019f020cb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a6ec67e-3178-4448-a662-1afe3bc99a80' class='xr-var-data-in' type='checkbox'><label for='data-0a6ec67e-3178-4448-a662-1afe3bc99a80' 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",
@@ -5406,7 +5674,7 @@
        "        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-b8f0e352-8343-4871-a499-681ea227177a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b8f0e352-8343-4871-a499-681ea227177a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b6a7ccc-3cb2-4283-8d8e-306048734fb8' class='xr-var-data-in' type='checkbox'><label for='data-9b6a7ccc-3cb2-4283-8d8e-306048734fb8' 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",
+       "        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-73119a11-a2b1-45ff-af13-969d5c93f7f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-73119a11-a2b1-45ff-af13-969d5c93f7f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c0a886f-a50a-4766-b1a5-218b5bb2eb92' class='xr-var-data-in' type='checkbox'><label for='data-5c0a886f-a50a-4766-b1a5-218b5bb2eb92' 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",
@@ -5429,19 +5697,48 @@
        "       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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-20bf9be4-47c4-4352-943d-9916137b2b11' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-20bf9be4-47c4-4352-943d-9916137b2b11' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71b987be-1751-4f22-a8bf-3082d5b1af02' class='xr-var-data-in' type='checkbox'><label for='data-71b987be-1751-4f22-a8bf-3082d5b1af02' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ad680399-7254-42f0-8e75-75e72a7ae4b4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ad680399-7254-42f0-8e75-75e72a7ae4b4' 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>"
+       "       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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1406f461-ede6-42c3-85e0-db98af548761' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1406f461-ede6-42c3-85e0-db98af548761' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30250d20-381f-465c-9a0b-fd09796392ac' class='xr-var-data-in' type='checkbox'><label for='data-30250d20-381f-465c-9a0b-fd09796392ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><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'>2010-01-01 03:00:00 ... 2015-01-...</div><input id='attrs-5250ed80-1335-436c-9bda-71a7cc7c0e2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5250ed80-1335-436c-9bda-71a7cc7c0e2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6d80735-0e37-46da-b74f-dd9964cb9d93' class='xr-var-data-in' type='checkbox'><label for='data-b6d80735-0e37-46da-b74f-dd9964cb9d93' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeProlepticGregorian(2010, 1, 1, 3, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeProlepticGregorian(2010, 1, 1, 6, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeProlepticGregorian(2010, 1, 1, 9, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeProlepticGregorian(2014, 12, 31, 18, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeProlepticGregorian(2014, 12, 31, 21, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeProlepticGregorian(2015, 1, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-239434a8-973b-4652-aec7-b15adb206c7b' class='xr-section-summary-in' type='checkbox'  ><label for='section-239434a8-973b-4652-aec7-b15adb206c7b' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6b1e9a39-e468-4a21-9dbf-c47c52e417c0' class='xr-index-data-in' type='checkbox'/><label for='index-6b1e9a39-e468-4a21-9dbf-c47c52e417c0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -90.0, -88.75,  -87.5, -86.25,  -85.0, -83.75,  -82.5, -81.25,  -80.0,\n",
+       "       -78.75,\n",
+       "       ...\n",
+       "        78.75,   80.0,  81.25,   82.5,  83.75,   85.0,  86.25,   87.5,  88.75,\n",
+       "         90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=145))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c2acd9b9-5ad8-460a-af7a-00562cbbe547' class='xr-index-data-in' type='checkbox'/><label for='index-c2acd9b9-5ad8-460a-af7a-00562cbbe547' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([    0.0,   1.875,    3.75,   5.625,     7.5,   9.375,   11.25,  13.125,\n",
+       "          15.0,  16.875,\n",
+       "       ...\n",
+       "        341.25, 343.125,   345.0, 346.875,  348.75, 350.625,   352.5, 354.375,\n",
+       "        356.25, 358.125],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ceef8ece-84e6-4144-968b-f488c406bce5' class='xr-index-data-in' type='checkbox'/><label for='index-ceef8ece-84e6-4144-968b-f488c406bce5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([2010-01-01 03:00:00, 2010-01-01 06:00:00, 2010-01-01 09:00:00,\n",
+       "             2010-01-01 12:00:00, 2010-01-01 15:00:00, 2010-01-01 18:00:00,\n",
+       "             2010-01-01 21:00:00, 2010-01-02 00:00:00, 2010-01-02 03:00:00,\n",
+       "             2010-01-02 06:00:00,\n",
+       "             ...\n",
+       "             2014-12-30 21:00:00, 2014-12-31 00:00:00, 2014-12-31 03:00:00,\n",
+       "             2014-12-31 06:00:00, 2014-12-31 09:00:00, 2014-12-31 12:00:00,\n",
+       "             2014-12-31 15:00:00, 2014-12-31 18:00:00, 2014-12-31 21:00:00,\n",
+       "             2015-01-01 00:00:00],\n",
+       "            dtype=&#x27;object&#x27;,\n",
+       "            length=14608,\n",
+       "            calendar=&#x27;proleptic_gregorian&#x27;,\n",
+       "            freq=&#x27;3h&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f7df7628-6571-426b-aef5-b57b824c0345' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f7df7628-6571-426b-aef5-b57b824c0345' 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 'tas' (time: 14608, lat: 145, lon: 192)>\n",
-       "dask.array<sub, shape=(14608, 145, 192), dtype=float32, chunksize=(913, 145, 192), chunktype=numpy.ndarray>\n",
+       "<xarray.DataArray 'tas' (time: 14608, lat: 145, lon: 192)> Size: 2GB\n",
+       "dask.array<sub, shape=(14608, 145, 192), dtype=float32, chunksize=(1205, 145, 192), chunktype=numpy.ndarray>\n",
        "Coordinates:\n",
-       "  * time     (time) datetime64[ns] 2010-01-01T03:00:00 ... 2015-01-01\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",
-       "    height   float64 ..."
+       "  * lat      (lat) float64 1kB -90.0 -88.75 -87.5 -86.25 ... 87.5 88.75 90.0\n",
+       "  * lon      (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 352.5 354.4 356.2 358.1\n",
+       "    height   float64 8B ...\n",
+       "  * time     (time) object 117kB 2010-01-01 03:00:00 ... 2015-01-01 00:00:00"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -5452,7 +5749,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5461,7 +5758,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -5728,6 +6025,11 @@
        "  grid-column: 4;\n",
        "}\n",
        "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
        ".xr-var-name,\n",
        ".xr-var-dims,\n",
        ".xr-var-dtype,\n",
@@ -5749,14 +6051,16 @@
        "}\n",
        "\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-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",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
        "  display: block;\n",
        "}\n",
        "\n",
@@ -5766,13 +6070,16 @@
        "\n",
        ".xr-var-name span,\n",
        ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
        ".xr-attrs {\n",
        "  padding-left: 25px !important;\n",
        "}\n",
        "\n",
        ".xr-attrs,\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
        "  grid-column: 1 / -1;\n",
        "}\n",
        "\n",
@@ -5810,7 +6117,8 @@
        "}\n",
        "\n",
        ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
        "  display: inline-block;\n",
        "  vertical-align: middle;\n",
        "  width: 1em;\n",
@@ -5819,21 +6127,21 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tas&#x27; (time: 1827, lat: 145, lon: 192)&gt;\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;tas&#x27; (time: 1827, lat: 145, lon: 192)&gt; Size: 407MB\n",
        "dask.array&lt;truediv, shape=(1827, 145, 192), dtype=float64, chunksize=(1, 145, 192), chunktype=numpy.ndarray&gt;\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",
-       "    height   float64 ...\n",
-       "  * time     (time) object 2010-01-01 00:00:00 ... 2015-01-01 00:00:00\n",
+       "  * lat      (lat) float64 1kB -90.0 -88.75 -87.5 -86.25 ... 87.5 88.75 90.0\n",
+       "  * lon      (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 352.5 354.4 356.2 358.1\n",
+       "    height   float64 8B ...\n",
+       "  * time     (time) object 15kB 2010-01-01 00:00:00 ... 2015-01-01 00:00:00\n",
        "Attributes:\n",
        "    operation:  temporal_avg\n",
        "    mode:       group_average\n",
        "    freq:       day\n",
-       "    weighted:   True</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'tas'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1827</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-94253089-1710-4b30-a96d-405b3e5c8466' class='xr-array-in' type='checkbox' checked><label for='section-94253089-1710-4b30-a96d-405b3e5c8466' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 145, 192), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
+       "    weighted:   True</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'tas'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1827</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-fae8b988-6558-4be9-a4b9-28d5774a692c' class='xr-array-in' type='checkbox' checked><label for='section-fae8b988-6558-4be9-a4b9-28d5774a692c' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 145, 192), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
        "    <tr>\n",
        "        <td>\n",
-       "            <table>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
        "                <thead>\n",
        "                    <tr>\n",
        "                        <td> </td>\n",
@@ -5855,14 +6163,12 @@
        "                        <td> (1, 145, 192) </td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
-       "                        <th> Count </th>\n",
-       "                        <td> 18283 Graph Layers </td>\n",
-       "                        <td> 1827 Chunks </td>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1827 chunks in 18293 graph layers </td>\n",
        "                    </tr>\n",
        "                    <tr>\n",
-       "                    <th> Type </th>\n",
-       "                    <td> float64 </td>\n",
-       "                    <td> numpy.ndarray </td>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
        "                    </tr>\n",
        "                </tbody>\n",
        "            </table>\n",
@@ -5946,7 +6252,7 @@
        "</svg>\n",
        "        </td>\n",
        "    </tr>\n",
-       "</table></div></div></li><li class='xr-section-item'><input id='section-fbc29c6e-1412-451d-b43c-91d5492943fc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fbc29c6e-1412-451d-b43c-91d5492943fc' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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-eef120fa-456d-4f27-ab0e-ef0f05bae45c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eef120fa-456d-4f27-ab0e-ef0f05bae45c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cc8c95e-4f52-4f42-b803-5c99b9766ae6' class='xr-var-data-in' type='checkbox'><label for='data-9cc8c95e-4f52-4f42-b803-5c99b9766ae6' 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",
+       "</table></div></div></li><li class='xr-section-item'><input id='section-263ba1ce-9073-4544-a2b7-8ea6e2bfe3bd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-263ba1ce-9073-4544-a2b7-8ea6e2bfe3bd' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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-27499397-42ed-4363-a320-1b36e93d6e58' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-27499397-42ed-4363-a320-1b36e93d6e58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c98d121e-655d-4f0b-b49d-7c9b4f6b433b' class='xr-var-data-in' type='checkbox'><label for='data-c98d121e-655d-4f0b-b49d-7c9b4f6b433b' 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",
@@ -5962,7 +6268,7 @@
        "        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-ac148f92-9d4b-49b9-95db-47ce0c576a9b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac148f92-9d4b-49b9-95db-47ce0c576a9b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0cc41f46-1a89-48f4-a564-7e53572afd71' class='xr-var-data-in' type='checkbox'><label for='data-0cc41f46-1a89-48f4-a564-7e53572afd71' 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",
+       "        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-4dd42519-900f-4f07-93e6-912f32a3ee2d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4dd42519-900f-4f07-93e6-912f32a3ee2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79dcc932-55c4-4ad0-b888-40fbc36e7e49' class='xr-var-data-in' type='checkbox'><label for='data-79dcc932-55c4-4ad0-b888-40fbc36e7e49' 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",
@@ -5985,23 +6291,45 @@
        "       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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3152eea7-ab37-44a7-b24b-14b230107ff4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3152eea7-ab37-44a7-b24b-14b230107ff4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e279bf5d-bc77-4543-9797-88e7180e11b4' class='xr-var-data-in' type='checkbox'><label for='data-e279bf5d-bc77-4543-9797-88e7180e11b4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</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'>object</div><div class='xr-var-preview xr-preview'>2010-01-01 00:00:00 ... 2015-01-...</div><input id='attrs-6ab8c8b0-b505-4b22-8b50-f9fe27a93e31' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ab8c8b0-b505-4b22-8b50-f9fe27a93e31' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d39fe360-d99a-4bbc-a5b7-016513776d60' class='xr-var-data-in' type='checkbox'><label for='data-d39fe360-d99a-4bbc-a5b7-016513776d60' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeProlepticGregorian(2010, 1, 1, 0, 0, 0, 0, has_year_zero=True),\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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e8b9b597-5c2c-49b9-86fd-574914ce51cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e8b9b597-5c2c-49b9-86fd-574914ce51cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d029aae5-ccac-4007-a1ca-c0c93467d82b' class='xr-var-data-in' type='checkbox'><label for='data-d029aae5-ccac-4007-a1ca-c0c93467d82b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><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'>2010-01-01 00:00:00 ... 2015-01-...</div><input id='attrs-a06baf98-1ec6-442f-9dd8-f00d48fad24d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a06baf98-1ec6-442f-9dd8-f00d48fad24d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a9e3557d-edcc-46d7-a3ce-27eec14551a4' class='xr-var-data-in' type='checkbox'><label for='data-a9e3557d-edcc-46d7-a3ce-27eec14551a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeProlepticGregorian(2010, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(2010, 1, 2, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(2010, 1, 3, 0, 0, 0, 0, has_year_zero=True),\n",
        "       ...,\n",
        "       cftime.DatetimeProlepticGregorian(2014, 12, 30, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(2014, 12, 31, 0, 0, 0, 0, has_year_zero=True),\n",
        "       cftime.DatetimeProlepticGregorian(2015, 1, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
-       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2e9f019c-fbcd-4c74-a8e9-88d1b85e8302' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2e9f019c-fbcd-4c74-a8e9-88d1b85e8302' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><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>day</dd><dt><span>weighted :</span></dt><dd>True</dd></dl></div></li></ul></div></div>"
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f9648fd7-5f88-4b9c-bf7c-0187847d5fb4' class='xr-section-summary-in' type='checkbox'  ><label for='section-f9648fd7-5f88-4b9c-bf7c-0187847d5fb4' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3f4c5948-6595-4e64-92dc-9d7f2e4bec7d' class='xr-index-data-in' type='checkbox'/><label for='index-3f4c5948-6595-4e64-92dc-9d7f2e4bec7d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -90.0, -88.75,  -87.5, -86.25,  -85.0, -83.75,  -82.5, -81.25,  -80.0,\n",
+       "       -78.75,\n",
+       "       ...\n",
+       "        78.75,   80.0,  81.25,   82.5,  83.75,   85.0,  86.25,   87.5,  88.75,\n",
+       "         90.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=145))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-fc11ddbf-aa25-4394-ba07-0dbc7f72ee6c' class='xr-index-data-in' type='checkbox'/><label for='index-fc11ddbf-aa25-4394-ba07-0dbc7f72ee6c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([    0.0,   1.875,    3.75,   5.625,     7.5,   9.375,   11.25,  13.125,\n",
+       "          15.0,  16.875,\n",
+       "       ...\n",
+       "        341.25, 343.125,   345.0, 346.875,  348.75, 350.625,   352.5, 354.375,\n",
+       "        356.25, 358.125],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4175c887-5635-496e-b650-0c72634cfad9' class='xr-index-data-in' type='checkbox'/><label for='index-4175c887-5635-496e-b650-0c72634cfad9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([2010-01-01 00:00:00, 2010-01-02 00:00:00, 2010-01-03 00:00:00,\n",
+       "             2010-01-04 00:00:00, 2010-01-05 00:00:00, 2010-01-06 00:00:00,\n",
+       "             2010-01-07 00:00:00, 2010-01-08 00:00:00, 2010-01-09 00:00:00,\n",
+       "             2010-01-10 00:00:00,\n",
+       "             ...\n",
+       "             2014-12-23 00:00:00, 2014-12-24 00:00:00, 2014-12-25 00:00:00,\n",
+       "             2014-12-26 00:00:00, 2014-12-27 00:00:00, 2014-12-28 00:00:00,\n",
+       "             2014-12-29 00:00:00, 2014-12-30 00:00:00, 2014-12-31 00:00:00,\n",
+       "             2015-01-01 00:00:00],\n",
+       "            dtype=&#x27;object&#x27;,\n",
+       "            length=1827,\n",
+       "            calendar=&#x27;proleptic_gregorian&#x27;,\n",
+       "            freq=&#x27;D&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e827f76a-a633-4369-a80d-c0980212f53e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e827f76a-a633-4369-a80d-c0980212f53e' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><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>day</dd><dt><span>weighted :</span></dt><dd>True</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
-       "<xarray.DataArray 'tas' (time: 1827, lat: 145, lon: 192)>\n",
+       "<xarray.DataArray 'tas' (time: 1827, lat: 145, lon: 192)> Size: 407MB\n",
        "dask.array<truediv, shape=(1827, 145, 192), dtype=float64, chunksize=(1, 145, 192), chunktype=numpy.ndarray>\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",
-       "    height   float64 ...\n",
-       "  * time     (time) object 2010-01-01 00:00:00 ... 2015-01-01 00:00:00\n",
+       "  * lat      (lat) float64 1kB -90.0 -88.75 -87.5 -86.25 ... 87.5 88.75 90.0\n",
+       "  * lon      (lon) float64 2kB 0.0 1.875 3.75 5.625 ... 352.5 354.4 356.2 358.1\n",
+       "    height   float64 8B ...\n",
+       "  * time     (time) object 15kB 2010-01-01 00:00:00 ... 2015-01-01 00:00:00\n",
        "Attributes:\n",
        "    operation:  temporal_avg\n",
        "    mode:       group_average\n",
@@ -6009,7 +6337,7 @@
        "    weighted:   True"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -6017,6 +6345,55 @@
    "source": [
     "ds3_day_avg.tas"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Visualize averages derived from 3-hourly data on a specific point\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# plot time series of temporal averages for a specific grid point: daily and monthly averages derived from 3-hourly time series\n",
+    "lat_point = 30\n",
+    "lon_point = 30\n",
+    "\n",
+    "start_year = \"2010-01-01\"\n",
+    "end_year = \"2014-12-31\"\n",
+    "\n",
+    "plt.figure(figsize=(10, 3))\n",
+    "ax = plt.subplot()\n",
+    "\n",
+    "ds2.tas.sel(lat=lat_point, lon=lon_point, time=slice(start_year, end_year)).plot(\n",
+    "    ax=ax, label=\"3-hourly (RAW DATA)\", alpha=0.5\n",
+    ")\n",
+    "ds3_day_avg.tas.sel(\n",
+    "    lat=lat_point, lon=lon_point, time=slice(start_year, end_year)\n",
+    ").plot(ax=ax, label=\"daily\", alpha=0.5)\n",
+    "ds2_monthly_avg.tas.sel(\n",
+    "    lat=lat_point, lon=lon_point, time=slice(start_year, end_year)\n",
+    ").plot(ax=ax, label=\"monthly\", alpha=0.5)\n",
+    "\n",
+    "plt.title(\"Daily and monthly averages derived from 3-hourly time series\")\n",
+    "plt.legend()\n",
+    "plt.tight_layout()"
+   ]
   }
  ],
  "metadata": {
@@ -6039,7 +6416,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.11.8"
   },
   "toc": {
    "base_numbering": 1,