section5_xrplus.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (time: 1828, lat: 90, lon: 180)&gt;\n",
       "[29613600 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean</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'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1828</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e5d45fc2-e92b-4e3b-8aa3-4f5ce6f4f24a' class='xr-array-in' type='checkbox' checked><label for='section-e5d45fc2-e92b-4e3b-8aa3-4f5ce6f4f24a' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[29613600 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-d7ab8a0f-0313-4b8d-8942-9fcbf44ce054' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d7ab8a0f-0313-4b8d-8942-9fcbf44ce054' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1870-01-16T12:00:00 ... 2022-04-...</div><input id='attrs-ddb4b451-8caf-4ea8-8ddb-ba38e369b338' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ddb4b451-8caf-4ea8-8ddb-ba38e369b338' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-077f44c2-3ab1-40fa-b37a-32be030c09bf' class='xr-var-data-in' type='checkbox'><label for='data-077f44c2-3ab1-40fa-b37a-32be030c09bf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1870-01-16T12:00:00.000000000&#x27;, &#x27;1870-02-14T23:59:59.011230469&#x27;,\n",
       "       &#x27;1870-03-16T11:59:58.681640625&#x27;, ..., &#x27;2022-02-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2022-03-16T12:00:00.000000000&#x27;, &#x27;2022-04-16T12:00:00.000000000&#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'>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 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-8328827f-3395-46d1-aac7-0ffb7d0c58b5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8328827f-3395-46d1-aac7-0ffb7d0c58b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2c30d81-dab8-4f73-8d2a-36a0ad3bd4e6' class='xr-var-data-in' type='checkbox'><label for='data-f2c30d81-dab8-4f73-8d2a-36a0ad3bd4e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-ece8d4ad-be25-4ef0-9f98-10ad37e0690a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ece8d4ad-be25-4ef0-9f98-10ad37e0690a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-572735c1-4fc6-4033-a400-4a6fc086c4d1' class='xr-var-data-in' type='checkbox'><label for='data-572735c1-4fc6-4033-a400-4a6fc086c4d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ed694b75-fe0d-4a1c-9171-d4b5c8b91e98' class='xr-section-summary-in' type='checkbox'  ><label for='section-ed694b75-fe0d-4a1c-9171-d4b5c8b91e98' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-100b56c9-95b1-4033-941f-3fe5e2b90a6d' class='xr-index-data-in' type='checkbox'/><label for='index-100b56c9-95b1-4033-941f-3fe5e2b90a6d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([          &#x27;1870-01-16 12:00:00&#x27;,\n",
       "               &#x27;1870-02-14 23:59:59.011230469&#x27;,\n",
       "               &#x27;1870-03-16 11:59:58.681640625&#x27;,\n",
       "               &#x27;1870-04-15 23:59:58.681640624&#x27;,\n",
       "                         &#x27;1870-05-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-06-16 00:00:00&#x27;,\n",
       "                         &#x27;1870-07-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-08-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-09-16 00:00:00&#x27;,\n",
       "                         &#x27;1870-10-16 12:00:00&#x27;,\n",
       "               ...\n",
       "                         &#x27;2021-07-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-08-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-09-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-10-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-11-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-12-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-01-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-02-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-03-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-04-16 12:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1828, freq=None))</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-21c6b8dc-0826-40d9-8ccd-2d8151c44074' class='xr-index-data-in' type='checkbox'/><label for='index-21c6b8dc-0826-40d9-8ccd-2d8151c44074' 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(Float64Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,\n",
       "               18.0,\n",
       "              ...\n",
       "              340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0,\n",
       "              358.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f5b95c77-7508-4aac-8401-d0d4fd87d1fb' class='xr-index-data-in' type='checkbox'/><label for='index-f5b95c77-7508-4aac-8401-d0d4fd87d1fb' 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(Float64Index([-89.0, -87.0, -85.0, -83.0, -81.0, -79.0, -77.0, -75.0, -73.0,\n",
       "              -71.0, -69.0, -67.0, -65.0, -63.0, -61.0, -59.0, -57.0, -55.0,\n",
       "              -53.0, -51.0, -49.0, -47.0, -45.0, -43.0, -41.0, -39.0, -37.0,\n",
       "              -35.0, -33.0, -31.0, -29.0, -27.0, -25.0, -23.0, -21.0, -19.0,\n",
       "              -17.0, -15.0, -13.0, -11.0,  -9.0,  -7.0,  -5.0,  -3.0,  -1.0,\n",
       "                1.0,   3.0,   5.0,   7.0,   9.0,  11.0,  13.0,  15.0,  17.0,\n",
       "               19.0,  21.0,  23.0,  25.0,  27.0,  29.0,  31.0,  33.0,  35.0,\n",
       "               37.0,  39.0,  41.0,  43.0,  45.0,  47.0,  49.0,  51.0,  53.0,\n",
       "               55.0,  57.0,  59.0,  61.0,  63.0,  65.0,  67.0,  69.0,  71.0,\n",
       "               73.0,  75.0,  77.0,  79.0,  81.0,  83.0,  85.0,  87.0,  89.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b9a4f5f2-731a-45e2-b539-3b257e5a904b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b9a4f5f2-731a-45e2-b539-3b257e5a904b' 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>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>C</dd><dt><span>cell_methods :</span></dt><dd>time: lat: lon: mean</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (time: 1828, lat: 90, lon: 180)>\n",
       "[29613600 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst = xr.open_dataset(\"../DATA/HadISST_sst_2x2.nc\")['sst']\n",
    "sst"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DataArrayGroupBy, grouped over 'lat'\n",
       "90 groups with labels -89.0, -87.0, ..., 87.0, 89.0."
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst.groupby(\"lat\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys([-89.0, -87.0, -85.0, -83.0, -81.0, -79.0, -77.0, -75.0, -73.0, -71.0, -69.0, -67.0, -65.0, -63.0, -61.0, -59.0, -57.0, -55.0, -53.0, -51.0, -49.0, -47.0, -45.0, -43.0, -41.0, -39.0, -37.0, -35.0, -33.0, -31.0, -29.0, -27.0, -25.0, -23.0, -21.0, -19.0, -17.0, -15.0, -13.0, -11.0, -9.0, -7.0, -5.0, -3.0, -1.0, 1.0, 3.0, 5.0, 7.0, 9.0, 11.0, 13.0, 15.0, 17.0, 19.0, 21.0, 23.0, 25.0, 27.0, 29.0, 31.0, 33.0, 35.0, 37.0, 39.0, 41.0, 43.0, 45.0, 47.0, 49.0, 51.0, 53.0, 55.0, 57.0, 59.0, 61.0, 63.0, 65.0, 67.0, 69.0, 71.0, 73.0, 75.0, 77.0, 79.0, 81.0, 83.0, 85.0, 87.0, 89.0])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dc = dict(sst.groupby(\"lat\"))\n",
    "dc.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_values([<xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -87.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -85.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -83.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -81.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -79.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -77.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -75.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -73.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -71.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -69.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -67.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -65.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -63.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -61.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -59.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -57.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -55.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -53.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -51.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -49.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -47.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -45.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -43.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -41.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -39.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -37.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -35.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -33.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -31.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -29.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -27.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -25.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -23.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -21.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -19.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -17.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -15.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -13.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -11.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -9.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -7.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -5.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -3.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -1.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 1.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 3.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 5.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 7.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 9.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 11.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 13.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 15.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 17.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 19.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 21.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 23.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 25.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 27.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 29.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 31.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 33.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 35.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 37.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 39.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 41.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 43.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 45.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 47.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 49.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 51.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 53.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 55.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 57.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 59.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 61.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 63.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 65.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 67.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 69.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 71.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 73.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 75.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 77.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 79.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 81.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 83.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 85.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 87.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean, <xarray.DataArray 'sst' (time: 1828, lon: 180)>\n",
       "[329040 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dc.values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "gb = sst.groupby(\"time.month\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dict(gb).keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Coordinates:\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "  * month    (month) int64 1 2 3 4 5 6 7 8 9 10 11 12"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sstmm = sst.groupby(\"time.month\").mean()\n",
    "sstmm.coords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (day: 3, lat: 90, lon: 180)&gt;\n",
       "array([[[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-251.35    ,   -1.8     ,   -1.8     , ...,   -1.8     ,\n",
       "           -1.8     ,   -1.8     ],\n",
       "        [  -1.8     ,   -1.8     ,   -1.8     , ..., -251.34999 ,\n",
       "           -1.8     ,   -1.8     ],\n",
       "        [-500.90002 , -500.90002 , -500.90002 , ..., -500.90002 ,\n",
       "         -500.90002 , -500.90002 ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "...\n",
       "        [-245.92493 ,  -48.816654,  -45.199924, ...,  -57.85831 ,\n",
       "          -54.241642,  -54.241642],\n",
       "        [ -52.433308,  -50.624977,  -50.624977, ..., -247.73328 ,\n",
       "          -54.241642,  -50.624977],\n",
       "        [-528.0244  , -528.0244  , -528.0244  , ..., -529.8327  ,\n",
       "         -529.8327  , -529.8328  ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-199.63458 , -126.05059 , -122.06127 , ..., -185.00616 ,\n",
       "         -234.79935 , -273.511   ],\n",
       "        [-178.36073 , -178.80394 , -209.39041 , ..., -169.20027 ,\n",
       "         -181.90755 , -210.12996 ],\n",
       "        [-435.30084 , -463.96246 , -462.7804  , ..., -467.50854 ,\n",
       "         -466.32666 , -431.45908 ]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "  * day      (day) int64 14 15 16\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean</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'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>day</span>: 3</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-9afb1bf5-4c5b-4141-be56-68b39eef006c' class='xr-array-in' type='checkbox' checked><label for='section-9afb1bf5-4c5b-4141-be56-68b39eef006c' 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>nan nan nan nan nan nan ... -504.7 -486.6 -436.2 -467.5 -466.3 -431.5</span></div><div class='xr-array-data'><pre>array([[[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-251.35    ,   -1.8     ,   -1.8     , ...,   -1.8     ,\n",
       "           -1.8     ,   -1.8     ],\n",
       "        [  -1.8     ,   -1.8     ,   -1.8     , ..., -251.34999 ,\n",
       "           -1.8     ,   -1.8     ],\n",
       "        [-500.90002 , -500.90002 , -500.90002 , ..., -500.90002 ,\n",
       "         -500.90002 , -500.90002 ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "...\n",
       "        [-245.92493 ,  -48.816654,  -45.199924, ...,  -57.85831 ,\n",
       "          -54.241642,  -54.241642],\n",
       "        [ -52.433308,  -50.624977,  -50.624977, ..., -247.73328 ,\n",
       "          -54.241642,  -50.624977],\n",
       "        [-528.0244  , -528.0244  , -528.0244  , ..., -529.8327  ,\n",
       "         -529.8327  , -529.8328  ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-199.63458 , -126.05059 , -122.06127 , ..., -185.00616 ,\n",
       "         -234.79935 , -273.511   ],\n",
       "        [-178.36073 , -178.80394 , -209.39041 , ..., -169.20027 ,\n",
       "         -181.90755 , -210.12996 ],\n",
       "        [-435.30084 , -463.96246 , -462.7804  , ..., -467.50854 ,\n",
       "         -466.32666 , -431.45908 ]]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-3ea213f1-6824-48d4-a666-3c6a54ced62d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3ea213f1-6824-48d4-a666-3c6a54ced62d' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-e63a55ce-a8cf-4007-a62f-5c8d99dfebd4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e63a55ce-a8cf-4007-a62f-5c8d99dfebd4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de001972-0a09-45b1-8391-c2a3079bbab9' class='xr-var-data-in' type='checkbox'><label for='data-de001972-0a09-45b1-8391-c2a3079bbab9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-0eed9b51-ac1a-4abc-91ac-a3f5568d349f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0eed9b51-ac1a-4abc-91ac-a3f5568d349f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4189051b-5bc0-443f-ab72-d2260e40867b' class='xr-var-data-in' type='checkbox'><label for='data-4189051b-5bc0-443f-ab72-d2260e40867b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>day</span></div><div class='xr-var-dims'>(day)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>14 15 16</div><input id='attrs-0cc76122-8f77-4449-97f8-c752df36fd59' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0cc76122-8f77-4449-97f8-c752df36fd59' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45734f35-a046-41b2-b6c9-60f2d5841848' class='xr-var-data-in' type='checkbox'><label for='data-45734f35-a046-41b2-b6c9-60f2d5841848' 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([14, 15, 16])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c3e1b62a-3541-4b43-a474-faad2a4d0406' class='xr-section-summary-in' type='checkbox'  ><label for='section-c3e1b62a-3541-4b43-a474-faad2a4d0406' 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>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-27e494ef-74a5-4ca4-b993-107da0c1c49f' class='xr-index-data-in' type='checkbox'/><label for='index-27e494ef-74a5-4ca4-b993-107da0c1c49f' 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(Float64Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,\n",
       "               18.0,\n",
       "              ...\n",
       "              340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0,\n",
       "              358.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1c6ed813-4f43-4f00-8be6-7b9112d7e18a' class='xr-index-data-in' type='checkbox'/><label for='index-1c6ed813-4f43-4f00-8be6-7b9112d7e18a' 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(Float64Index([-89.0, -87.0, -85.0, -83.0, -81.0, -79.0, -77.0, -75.0, -73.0,\n",
       "              -71.0, -69.0, -67.0, -65.0, -63.0, -61.0, -59.0, -57.0, -55.0,\n",
       "              -53.0, -51.0, -49.0, -47.0, -45.0, -43.0, -41.0, -39.0, -37.0,\n",
       "              -35.0, -33.0, -31.0, -29.0, -27.0, -25.0, -23.0, -21.0, -19.0,\n",
       "              -17.0, -15.0, -13.0, -11.0,  -9.0,  -7.0,  -5.0,  -3.0,  -1.0,\n",
       "                1.0,   3.0,   5.0,   7.0,   9.0,  11.0,  13.0,  15.0,  17.0,\n",
       "               19.0,  21.0,  23.0,  25.0,  27.0,  29.0,  31.0,  33.0,  35.0,\n",
       "               37.0,  39.0,  41.0,  43.0,  45.0,  47.0,  49.0,  51.0,  53.0,\n",
       "               55.0,  57.0,  59.0,  61.0,  63.0,  65.0,  67.0,  69.0,  71.0,\n",
       "               73.0,  75.0,  77.0,  79.0,  81.0,  83.0,  85.0,  87.0,  89.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>day</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-af860fa4-671d-4fce-9506-c6642e058a0a' class='xr-index-data-in' type='checkbox'/><label for='index-af860fa4-671d-4fce-9506-c6642e058a0a' 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(Int64Index([14, 15, 16], dtype=&#x27;int64&#x27;, name=&#x27;day&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7666970d-ab0a-4342-9ba0-135ac64d7e31' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7666970d-ab0a-4342-9ba0-135ac64d7e31' 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>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>C</dd><dt><span>cell_methods :</span></dt><dd>time: lat: lon: mean</dd></dl></div></li></ul></div></div>"
      ],
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       "<xarray.DataArray 'sst' (day: 3, lat: 90, lon: 180)>\n",
       "array([[[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-251.35    ,   -1.8     ,   -1.8     , ...,   -1.8     ,\n",
       "           -1.8     ,   -1.8     ],\n",
       "        [  -1.8     ,   -1.8     ,   -1.8     , ..., -251.34999 ,\n",
       "           -1.8     ,   -1.8     ],\n",
       "        [-500.90002 , -500.90002 , -500.90002 , ..., -500.90002 ,\n",
       "         -500.90002 , -500.90002 ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "...\n",
       "        [-245.92493 ,  -48.816654,  -45.199924, ...,  -57.85831 ,\n",
       "          -54.241642,  -54.241642],\n",
       "        [ -52.433308,  -50.624977,  -50.624977, ..., -247.73328 ,\n",
       "          -54.241642,  -50.624977],\n",
       "        [-528.0244  , -528.0244  , -528.0244  , ..., -529.8327  ,\n",
       "         -529.8327  , -529.8328  ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-199.63458 , -126.05059 , -122.06127 , ..., -185.00616 ,\n",
       "         -234.79935 , -273.511   ],\n",
       "        [-178.36073 , -178.80394 , -209.39041 , ..., -169.20027 ,\n",
       "         -181.90755 , -210.12996 ],\n",
       "        [-435.30084 , -463.96246 , -462.7804  , ..., -467.50854 ,\n",
       "         -466.32666 , -431.45908 ]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "  * day      (day) int64 14 15 16\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sstdm = sst.groupby(\"time.day\").mean()\n",
    "sstdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
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       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-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",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".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-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-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-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (season: 4, lat: 90, lon: 180)&gt;\n",
       "array([[[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-106.41506 ,  -45.389584,  -85.70994 , ...,  -57.9216  ,\n",
       "         -115.13296 ,  -49.748528],\n",
       "        [-126.5752  ,  -68.81893 ,  -66.63949 , ..., -133.6585  ,\n",
       "         -129.84439 , -124.94058 ],\n",
       "        [-533.0483  , -531.4139  , -529.23444 , ..., -537.9522  ,\n",
       "         -535.7727  , -530.32404 ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "...\n",
       "        [-223.0161  , -161.44649 , -163.62593 , ..., -362.5025  ,\n",
       "         -360.86783 , -409.9067  ],\n",
       "        [-313.46384 , -314.5536  , -254.07378 , ..., -203.94649 ,\n",
       "         -260.06735 , -310.73947 ],\n",
       "        [-556.4776  , -548.3046  , -545.03546 , ..., -554.29816 ,\n",
       "         -554.29816 , -552.1187  ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-367.3639  , -190.59764 , -130.94681 , ..., -194.97867 ,\n",
       "         -372.29037 , -430.29938 ],\n",
       "        [-194.98016 , -254.08376 , -374.48212 , ..., -316.47217 ,\n",
       "         -256.2733  , -315.37747 ],\n",
       "        [-444.5324  , -562.7415  , -563.2888  , ..., -563.2888  ,\n",
       "         -563.2888  , -442.89066 ]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "  * season   (season) object &#x27;DJF&#x27; &#x27;JJA&#x27; &#x27;MAM&#x27; &#x27;SON&#x27;\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean</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'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>season</span>: 4</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-3617d913-db15-4868-892a-31febda24008' class='xr-array-in' type='checkbox' checked><label for='section-3617d913-db15-4868-892a-31febda24008' 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>nan nan nan nan nan nan ... -564.9 -564.4 -445.1 -563.3 -563.3 -442.9</span></div><div class='xr-array-data'><pre>array([[[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-106.41506 ,  -45.389584,  -85.70994 , ...,  -57.9216  ,\n",
       "         -115.13296 ,  -49.748528],\n",
       "        [-126.5752  ,  -68.81893 ,  -66.63949 , ..., -133.6585  ,\n",
       "         -129.84439 , -124.94058 ],\n",
       "        [-533.0483  , -531.4139  , -529.23444 , ..., -537.9522  ,\n",
       "         -535.7727  , -530.32404 ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "...\n",
       "        [-223.0161  , -161.44649 , -163.62593 , ..., -362.5025  ,\n",
       "         -360.86783 , -409.9067  ],\n",
       "        [-313.46384 , -314.5536  , -254.07378 , ..., -203.94649 ,\n",
       "         -260.06735 , -310.73947 ],\n",
       "        [-556.4776  , -548.3046  , -545.03546 , ..., -554.29816 ,\n",
       "         -554.29816 , -552.1187  ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-367.3639  , -190.59764 , -130.94681 , ..., -194.97867 ,\n",
       "         -372.29037 , -430.29938 ],\n",
       "        [-194.98016 , -254.08376 , -374.48212 , ..., -316.47217 ,\n",
       "         -256.2733  , -315.37747 ],\n",
       "        [-444.5324  , -562.7415  , -563.2888  , ..., -563.2888  ,\n",
       "         -563.2888  , -442.89066 ]]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-ec932280-f2ac-465b-8123-400f97a94c5c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ec932280-f2ac-465b-8123-400f97a94c5c' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-a4d32b23-a3c0-45fe-8529-6ddbbbc86a77' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a4d32b23-a3c0-45fe-8529-6ddbbbc86a77' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b7ab5e2-f5d3-4bf2-b696-fdfdf7c2612e' class='xr-var-data-in' type='checkbox'><label for='data-1b7ab5e2-f5d3-4bf2-b696-fdfdf7c2612e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-1c8dd618-5d65-4d56-9117-d54bc3c32767' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c8dd618-5d65-4d56-9117-d54bc3c32767' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71007e7c-a310-4ae4-addb-b583aea22344' class='xr-var-data-in' type='checkbox'><label for='data-71007e7c-a310-4ae4-addb-b583aea22344' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>season</span></div><div class='xr-var-dims'>(season)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;DJF&#x27; &#x27;JJA&#x27; &#x27;MAM&#x27; &#x27;SON&#x27;</div><input id='attrs-773bd38c-e1a6-4f2a-a63a-f0d74dec91f0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-773bd38c-e1a6-4f2a-a63a-f0d74dec91f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46c99df1-60ff-4908-83f6-55aef1b0b3ae' class='xr-var-data-in' type='checkbox'><label for='data-46c99df1-60ff-4908-83f6-55aef1b0b3ae' 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([&#x27;DJF&#x27;, &#x27;JJA&#x27;, &#x27;MAM&#x27;, &#x27;SON&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a0dc1d07-4b39-43ff-afc0-041a34f47f0f' class='xr-section-summary-in' type='checkbox'  ><label for='section-a0dc1d07-4b39-43ff-afc0-041a34f47f0f' 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>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ad5d2bee-9441-483a-b85f-c6f6990cbc92' class='xr-index-data-in' type='checkbox'/><label for='index-ad5d2bee-9441-483a-b85f-c6f6990cbc92' 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(Float64Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,\n",
       "               18.0,\n",
       "              ...\n",
       "              340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0,\n",
       "              358.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0e63ef6b-e481-4936-82e8-563cd1303f76' class='xr-index-data-in' type='checkbox'/><label for='index-0e63ef6b-e481-4936-82e8-563cd1303f76' 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(Float64Index([-89.0, -87.0, -85.0, -83.0, -81.0, -79.0, -77.0, -75.0, -73.0,\n",
       "              -71.0, -69.0, -67.0, -65.0, -63.0, -61.0, -59.0, -57.0, -55.0,\n",
       "              -53.0, -51.0, -49.0, -47.0, -45.0, -43.0, -41.0, -39.0, -37.0,\n",
       "              -35.0, -33.0, -31.0, -29.0, -27.0, -25.0, -23.0, -21.0, -19.0,\n",
       "              -17.0, -15.0, -13.0, -11.0,  -9.0,  -7.0,  -5.0,  -3.0,  -1.0,\n",
       "                1.0,   3.0,   5.0,   7.0,   9.0,  11.0,  13.0,  15.0,  17.0,\n",
       "               19.0,  21.0,  23.0,  25.0,  27.0,  29.0,  31.0,  33.0,  35.0,\n",
       "               37.0,  39.0,  41.0,  43.0,  45.0,  47.0,  49.0,  51.0,  53.0,\n",
       "               55.0,  57.0,  59.0,  61.0,  63.0,  65.0,  67.0,  69.0,  71.0,\n",
       "               73.0,  75.0,  77.0,  79.0,  81.0,  83.0,  85.0,  87.0,  89.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>season</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5e66455e-6512-4c55-9d90-1433b3bc0255' class='xr-index-data-in' type='checkbox'/><label for='index-5e66455e-6512-4c55-9d90-1433b3bc0255' 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([&#x27;DJF&#x27;, &#x27;JJA&#x27;, &#x27;MAM&#x27;, &#x27;SON&#x27;], dtype=&#x27;object&#x27;, name=&#x27;season&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1959863c-6d06-492c-a323-e0ab7885fbc5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1959863c-6d06-492c-a323-e0ab7885fbc5' 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>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>C</dd><dt><span>cell_methods :</span></dt><dd>time: lat: lon: mean</dd></dl></div></li></ul></div></div>"
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       "...\n",
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       "         -360.86783 , -409.9067  ],\n",
       "        [-313.46384 , -314.5536  , -254.07378 , ..., -203.94649 ,\n",
       "         -260.06735 , -310.73947 ],\n",
       "        [-556.4776  , -548.3046  , -545.03546 , ..., -554.29816 ,\n",
       "         -554.29816 , -552.1187  ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
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       "                 nan,         nan],\n",
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       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-367.3639  , -190.59764 , -130.94681 , ..., -194.97867 ,\n",
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       "        [-194.98016 , -254.08376 , -374.48212 , ..., -316.47217 ,\n",
       "         -256.2733  , -315.37747 ],\n",
       "        [-444.5324  , -562.7415  , -563.2888  , ..., -563.2888  ,\n",
       "         -563.2888  , -442.89066 ]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "  * season   (season) object 'DJF' 'JJA' 'MAM' 'SON'\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst.groupby(\"time.season\").mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
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       "        [285.64725, 216.11565, 142.10825, ..., 219.79567, 285.27682,\n",
       "         371.1242 ],\n",
       "        [326.74332, 430.48492, 284.81497, ..., 221.71494, 256.7846 ,\n",
       "         327.0032 ],\n",
       "        [389.3    , 303.16684, 302.8291 , ..., 302.8291 , 302.8291 ,\n",
       "         389.93512]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "  * season   (season) object &#x27;DJF&#x27; &#x27;JJA&#x27; &#x27;MAM&#x27; &#x27;SON&#x27;\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean</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'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>season</span>: 4</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-174c2117-e611-4a8c-b11a-af44049fb7e6' class='xr-array-in' type='checkbox' checked><label for='section-174c2117-e611-4a8c-b11a-af44049fb7e6' 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>nan nan nan nan nan nan nan ... 303.6 303.5 183.0 302.8 302.8 389.9</span></div><div class='xr-array-data'><pre>array([[[      nan,       nan,       nan, ...,       nan,       nan,\n",
       "               nan],\n",
       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
       "               nan],\n",
       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
       "               nan],\n",
       "        ...,\n",
       "        [206.46713, 190.9033 , 197.9637 , ..., 215.59273, 223.55026,\n",
       "         193.4033 ],\n",
       "        [236.25511, 237.82341, 230.89392, ..., 252.29482, 245.82295,\n",
       "         237.97005],\n",
       "        [175.84088, 170.24344, 168.21193, ..., 176.03568, 174.15361,\n",
       "         171.23119]],\n",
       "\n",
       "       [[      nan,       nan,       nan, ...,       nan,       nan,\n",
       "               nan],\n",
       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
       "               nan],\n",
       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
       "               nan],\n",
       "...\n",
       "        [244.06715, 259.0563 , 257.17224, ..., 340.99106, 342.5125 ,\n",
       "         377.86963],\n",
       "        [293.0584 , 293.28918, 266.14655, ..., 244.17255, 271.33154,\n",
       "         292.46298],\n",
       "        [178.86311, 187.47057, 183.88263, ..., 189.83344, 189.11581,\n",
       "         186.82892]],\n",
       "\n",
       "       [[      nan,       nan,       nan, ...,       nan,       nan,\n",
       "               nan],\n",
       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
       "               nan],\n",
       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
       "               nan],\n",
       "        ...,\n",
       "        [285.64725, 216.11565, 142.10825, ..., 219.79567, 285.27682,\n",
       "         371.1242 ],\n",
       "        [326.74332, 430.48492, 284.81497, ..., 221.71494, 256.7846 ,\n",
       "         327.0032 ],\n",
       "        [389.3    , 303.16684, 302.8291 , ..., 302.8291 , 302.8291 ,\n",
       "         389.93512]]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-1afef652-5f5e-4853-9da4-437d7ddee10f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1afef652-5f5e-4853-9da4-437d7ddee10f' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-e4b0c6ac-6ac8-4e48-9579-f3e2d3a7249c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e4b0c6ac-6ac8-4e48-9579-f3e2d3a7249c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bfdc61d2-0c9c-4f4b-8a03-206b1ccde63f' class='xr-var-data-in' type='checkbox'><label for='data-bfdc61d2-0c9c-4f4b-8a03-206b1ccde63f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-af7679b3-0c32-486f-b83b-0ba9510220fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af7679b3-0c32-486f-b83b-0ba9510220fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f33890ef-294d-41d6-9d7e-f8898b0695f7' class='xr-var-data-in' type='checkbox'><label for='data-f33890ef-294d-41d6-9d7e-f8898b0695f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>season</span></div><div class='xr-var-dims'>(season)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;DJF&#x27; &#x27;JJA&#x27; &#x27;MAM&#x27; &#x27;SON&#x27;</div><input id='attrs-9250fc32-bd36-4fe9-8e5b-8246cabceaea' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9250fc32-bd36-4fe9-8e5b-8246cabceaea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5237b157-0bec-47b0-a000-72e13ecd656e' class='xr-var-data-in' type='checkbox'><label for='data-5237b157-0bec-47b0-a000-72e13ecd656e' 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([&#x27;DJF&#x27;, &#x27;JJA&#x27;, &#x27;MAM&#x27;, &#x27;SON&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-789397cf-9953-4d4a-b088-da025518f3ed' class='xr-section-summary-in' type='checkbox'  ><label for='section-789397cf-9953-4d4a-b088-da025518f3ed' 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>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3087f4a9-f05d-4fa6-8cb0-252ac328ac47' class='xr-index-data-in' type='checkbox'/><label for='index-3087f4a9-f05d-4fa6-8cb0-252ac328ac47' 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(Float64Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,\n",
       "               18.0,\n",
       "              ...\n",
       "              340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0,\n",
       "              358.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-13cddda3-fcae-4d66-a254-b7ad818f89e8' class='xr-index-data-in' type='checkbox'/><label for='index-13cddda3-fcae-4d66-a254-b7ad818f89e8' 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(Float64Index([-89.0, -87.0, -85.0, -83.0, -81.0, -79.0, -77.0, -75.0, -73.0,\n",
       "              -71.0, -69.0, -67.0, -65.0, -63.0, -61.0, -59.0, -57.0, -55.0,\n",
       "              -53.0, -51.0, -49.0, -47.0, -45.0, -43.0, -41.0, -39.0, -37.0,\n",
       "              -35.0, -33.0, -31.0, -29.0, -27.0, -25.0, -23.0, -21.0, -19.0,\n",
       "              -17.0, -15.0, -13.0, -11.0,  -9.0,  -7.0,  -5.0,  -3.0,  -1.0,\n",
       "                1.0,   3.0,   5.0,   7.0,   9.0,  11.0,  13.0,  15.0,  17.0,\n",
       "               19.0,  21.0,  23.0,  25.0,  27.0,  29.0,  31.0,  33.0,  35.0,\n",
       "               37.0,  39.0,  41.0,  43.0,  45.0,  47.0,  49.0,  51.0,  53.0,\n",
       "               55.0,  57.0,  59.0,  61.0,  63.0,  65.0,  67.0,  69.0,  71.0,\n",
       "               73.0,  75.0,  77.0,  79.0,  81.0,  83.0,  85.0,  87.0,  89.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>season</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cbb5edf6-fc80-4513-92ec-fd2af0126217' class='xr-index-data-in' type='checkbox'/><label for='index-cbb5edf6-fc80-4513-92ec-fd2af0126217' 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([&#x27;DJF&#x27;, &#x27;JJA&#x27;, &#x27;MAM&#x27;, &#x27;SON&#x27;], dtype=&#x27;object&#x27;, name=&#x27;season&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0c704bf0-0e28-433f-aaaa-67fa3f14da91' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0c704bf0-0e28-433f-aaaa-67fa3f14da91' 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>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>C</dd><dt><span>cell_methods :</span></dt><dd>time: lat: lon: mean</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (season: 4, lat: 90, lon: 180)>\n",
       "array([[[      nan,       nan,       nan, ...,       nan,       nan,\n",
       "               nan],\n",
       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
       "               nan],\n",
       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
       "               nan],\n",
       "        ...,\n",
       "        [206.46713, 190.9033 , 197.9637 , ..., 215.59273, 223.55026,\n",
       "         193.4033 ],\n",
       "        [236.25511, 237.82341, 230.89392, ..., 252.29482, 245.82295,\n",
       "         237.97005],\n",
       "        [175.84088, 170.24344, 168.21193, ..., 176.03568, 174.15361,\n",
       "         171.23119]],\n",
       "\n",
       "       [[      nan,       nan,       nan, ...,       nan,       nan,\n",
       "               nan],\n",
       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
       "               nan],\n",
       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
       "               nan],\n",
       "...\n",
       "        [244.06715, 259.0563 , 257.17224, ..., 340.99106, 342.5125 ,\n",
       "         377.86963],\n",
       "        [293.0584 , 293.28918, 266.14655, ..., 244.17255, 271.33154,\n",
       "         292.46298],\n",
       "        [178.86311, 187.47057, 183.88263, ..., 189.83344, 189.11581,\n",
       "         186.82892]],\n",
       "\n",
       "       [[      nan,       nan,       nan, ...,       nan,       nan,\n",
       "               nan],\n",
       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
       "               nan],\n",
       "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
       "               nan],\n",
       "        ...,\n",
       "        [285.64725, 216.11565, 142.10825, ..., 219.79567, 285.27682,\n",
       "         371.1242 ],\n",
       "        [326.74332, 430.48492, 284.81497, ..., 221.71494, 256.7846 ,\n",
       "         327.0032 ],\n",
       "        [389.3    , 303.16684, 302.8291 , ..., 302.8291 , 302.8291 ,\n",
       "         389.93512]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "  * season   (season) object 'DJF' 'JJA' 'MAM' 'SON'\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst.groupby(\"time.season\").std() # std"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1828, 90, 180, 12)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get anomaly\n",
    "\n",
    "sstmm = sst.groupby(\"time.month\").mean()\n",
    "(sst - sstmm).shape # 对吗？"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Coordinates:\n",
       "   * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "   * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "   * month    (month) int64 1 2 3 4 5 6 7 8 9 10 11 12,\n",
       " (12, 90, 180))"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sstmm.coords,sstmm.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body[data-theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-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",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".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-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-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-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (time: 1828, lat: 90, lon: 180)&gt;\n",
       "array([[[         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        ...,\n",
       "        [  45.669262 ,   44.03821  ,  161.47363  , ...,   55.45553  ,\n",
       "           53.82449  ,   50.562397 ],\n",
       "        [  71.76599  ,   79.92123  ,   78.29018  , ...,   75.02808  ,\n",
       "           70.13494  ,   68.5039   ],\n",
       "        [  45.668762 ,   45.66864  ,   44.037598 , ...,   50.561768 ,\n",
       "           48.930786 ,   44.037598 ]],\n",
       "\n",
       "       [[         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "...\n",
       "        [ 156.58025  ,  399.60605  ,  -96.2319   , ...,  177.78378  ,\n",
       "          179.41487  ,  600.22437  ],\n",
       "        [ -68.50418  , -316.4231   , -565.973    , ..., -233.23962  ,\n",
       "          -57.087067 ,  -68.50418  ],\n",
       "        [-185.9397   , -445.27606  , -455.06232  , ..., -433.8587   ,\n",
       "         -433.85876  , -437.12085  ]],\n",
       "\n",
       "       [[         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        ...,\n",
       "        [-283.802    , -464.84808  , -707.8739   , ...,   88.07599  ,\n",
       "           81.5517   ,  572.49646  ],\n",
       "        [-569.2351   , -574.1283   , -750.2811   , ..., -740.4949   ,\n",
       "         -742.12585  , -572.49725  ],\n",
       "        [-192.46387  ,   52.1929   ,   50.56186  , ..., -440.383    ,\n",
       "         -438.7519   ,   53.823944 ]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "    month    (time) int64 1 2 3 4 5 6 7 8 9 10 11 ... 6 7 8 9 10 11 12 1 2 3 4</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'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1828</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-c0bf817c-60ab-4f10-821e-a44ed5c6c5d9' class='xr-array-in' type='checkbox' checked><label for='section-c0bf817c-60ab-4f10-821e-a44ed5c6c5d9' 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>nan nan nan nan nan nan ... -437.1 -432.2 -437.1 -440.4 -438.8 53.82</span></div><div class='xr-array-data'><pre>array([[[         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        ...,\n",
       "        [  45.669262 ,   44.03821  ,  161.47363  , ...,   55.45553  ,\n",
       "           53.82449  ,   50.562397 ],\n",
       "        [  71.76599  ,   79.92123  ,   78.29018  , ...,   75.02808  ,\n",
       "           70.13494  ,   68.5039   ],\n",
       "        [  45.668762 ,   45.66864  ,   44.037598 , ...,   50.561768 ,\n",
       "           48.930786 ,   44.037598 ]],\n",
       "\n",
       "       [[         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "...\n",
       "        [ 156.58025  ,  399.60605  ,  -96.2319   , ...,  177.78378  ,\n",
       "          179.41487  ,  600.22437  ],\n",
       "        [ -68.50418  , -316.4231   , -565.973    , ..., -233.23962  ,\n",
       "          -57.087067 ,  -68.50418  ],\n",
       "        [-185.9397   , -445.27606  , -455.06232  , ..., -433.8587   ,\n",
       "         -433.85876  , -437.12085  ]],\n",
       "\n",
       "       [[         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        ...,\n",
       "        [-283.802    , -464.84808  , -707.8739   , ...,   88.07599  ,\n",
       "           81.5517   ,  572.49646  ],\n",
       "        [-569.2351   , -574.1283   , -750.2811   , ..., -740.4949   ,\n",
       "         -742.12585  , -572.49725  ],\n",
       "        [-192.46387  ,   52.1929   ,   50.56186  , ..., -440.383    ,\n",
       "         -438.7519   ,   53.823944 ]]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-7016d1c1-e802-41cf-a4d1-2149cdb4c376' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7016d1c1-e802-41cf-a4d1-2149cdb4c376' 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'>1870-01-16T12:00:00 ... 2022-04-...</div><input id='attrs-b96f901a-b9f0-474e-b5cd-ceb681563fca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b96f901a-b9f0-474e-b5cd-ceb681563fca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a287d107-3b8d-4d15-a9aa-9db09e3db3b4' class='xr-var-data-in' type='checkbox'><label for='data-a287d107-3b8d-4d15-a9aa-9db09e3db3b4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1870-01-16T12:00:00.000000000&#x27;, &#x27;1870-02-14T23:59:59.011230469&#x27;,\n",
       "       &#x27;1870-03-16T11:59:58.681640625&#x27;, ..., &#x27;2022-02-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2022-03-16T12:00:00.000000000&#x27;, &#x27;2022-04-16T12:00:00.000000000&#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'>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 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-c21db993-980a-4676-8bcb-73a003ab897e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c21db993-980a-4676-8bcb-73a003ab897e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c453cf25-6ad7-4e3f-a3b1-af5bf295fbec' class='xr-var-data-in' type='checkbox'><label for='data-c453cf25-6ad7-4e3f-a3b1-af5bf295fbec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-0c611885-2665-448e-8682-e3d4812e8862' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c611885-2665-448e-8682-e3d4812e8862' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-866ea545-2d9e-49e2-943a-5cf54ce1ad06' class='xr-var-data-in' type='checkbox'><label for='data-866ea545-2d9e-49e2-943a-5cf54ce1ad06' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>month</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 ... 10 11 12 1 2 3 4</div><input id='attrs-430d5e35-8a42-4fc9-810f-e2f1919fe5d9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-430d5e35-8a42-4fc9-810f-e2f1919fe5d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e962d25-c346-4f8d-b832-447f0827261c' class='xr-var-data-in' type='checkbox'><label for='data-1e962d25-c346-4f8d-b832-447f0827261c' 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([1, 2, 3, ..., 2, 3, 4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8bebe4fd-454b-4177-b20b-76b82a87f193' class='xr-section-summary-in' type='checkbox'  ><label for='section-8bebe4fd-454b-4177-b20b-76b82a87f193' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-708c3d5d-8dd0-4810-b87f-8e3c33e5aa26' class='xr-index-data-in' type='checkbox'/><label for='index-708c3d5d-8dd0-4810-b87f-8e3c33e5aa26' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([          &#x27;1870-01-16 12:00:00&#x27;,\n",
       "               &#x27;1870-02-14 23:59:59.011230469&#x27;,\n",
       "               &#x27;1870-03-16 11:59:58.681640625&#x27;,\n",
       "               &#x27;1870-04-15 23:59:58.681640624&#x27;,\n",
       "                         &#x27;1870-05-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-06-16 00:00:00&#x27;,\n",
       "                         &#x27;1870-07-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-08-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-09-16 00:00:00&#x27;,\n",
       "                         &#x27;1870-10-16 12:00:00&#x27;,\n",
       "               ...\n",
       "                         &#x27;2021-07-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-08-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-09-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-10-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-11-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-12-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-01-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-02-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-03-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-04-16 12:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1828, freq=None))</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-dc3f88ef-7589-49f3-9faf-10fcf102efc6' class='xr-index-data-in' type='checkbox'/><label for='index-dc3f88ef-7589-49f3-9faf-10fcf102efc6' 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(Float64Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,\n",
       "               18.0,\n",
       "              ...\n",
       "              340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0,\n",
       "              358.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a5313ce2-febb-4ead-bad0-e249e21f9015' class='xr-index-data-in' type='checkbox'/><label for='index-a5313ce2-febb-4ead-bad0-e249e21f9015' 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(Float64Index([-89.0, -87.0, -85.0, -83.0, -81.0, -79.0, -77.0, -75.0, -73.0,\n",
       "              -71.0, -69.0, -67.0, -65.0, -63.0, -61.0, -59.0, -57.0, -55.0,\n",
       "              -53.0, -51.0, -49.0, -47.0, -45.0, -43.0, -41.0, -39.0, -37.0,\n",
       "              -35.0, -33.0, -31.0, -29.0, -27.0, -25.0, -23.0, -21.0, -19.0,\n",
       "              -17.0, -15.0, -13.0, -11.0,  -9.0,  -7.0,  -5.0,  -3.0,  -1.0,\n",
       "                1.0,   3.0,   5.0,   7.0,   9.0,  11.0,  13.0,  15.0,  17.0,\n",
       "               19.0,  21.0,  23.0,  25.0,  27.0,  29.0,  31.0,  33.0,  35.0,\n",
       "               37.0,  39.0,  41.0,  43.0,  45.0,  47.0,  49.0,  51.0,  53.0,\n",
       "               55.0,  57.0,  59.0,  61.0,  63.0,  65.0,  67.0,  69.0,  71.0,\n",
       "               73.0,  75.0,  77.0,  79.0,  81.0,  83.0,  85.0,  87.0,  89.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-be868302-a580-46e1-a36d-4084053f570a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-be868302-a580-46e1-a36d-4084053f570a' 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 'sst' (time: 1828, lat: 90, lon: 180)>\n",
       "array([[[         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        ...,\n",
       "        [  45.669262 ,   44.03821  ,  161.47363  , ...,   55.45553  ,\n",
       "           53.82449  ,   50.562397 ],\n",
       "        [  71.76599  ,   79.92123  ,   78.29018  , ...,   75.02808  ,\n",
       "           70.13494  ,   68.5039   ],\n",
       "        [  45.668762 ,   45.66864  ,   44.037598 , ...,   50.561768 ,\n",
       "           48.930786 ,   44.037598 ]],\n",
       "\n",
       "       [[         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "...\n",
       "        [ 156.58025  ,  399.60605  ,  -96.2319   , ...,  177.78378  ,\n",
       "          179.41487  ,  600.22437  ],\n",
       "        [ -68.50418  , -316.4231   , -565.973    , ..., -233.23962  ,\n",
       "          -57.087067 ,  -68.50418  ],\n",
       "        [-185.9397   , -445.27606  , -455.06232  , ..., -433.8587   ,\n",
       "         -433.85876  , -437.12085  ]],\n",
       "\n",
       "       [[         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        ...,\n",
       "        [-283.802    , -464.84808  , -707.8739   , ...,   88.07599  ,\n",
       "           81.5517   ,  572.49646  ],\n",
       "        [-569.2351   , -574.1283   , -750.2811   , ..., -740.4949   ,\n",
       "         -742.12585  , -572.49725  ],\n",
       "        [-192.46387  ,   52.1929   ,   50.56186  , ..., -440.383    ,\n",
       "         -438.7519   ,   53.823944 ]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "    month    (time) int64 1 2 3 4 5 6 7 8 9 10 11 ... 6 7 8 9 10 11 12 1 2 3 4"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ssta = sst.groupby(\"time.month\") -sstmm\n",
    "ssta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;month&#x27; (time: 1828)&gt;\n",
       "array([1, 2, 3, ..., 2, 3, 4])\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'month'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1828</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-503f2869-9383-4eb5-ae0e-76d40bf98832' class='xr-array-in' type='checkbox' checked><label for='section-503f2869-9383-4eb5-ae0e-76d40bf98832' 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>1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 ... 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4</span></div><div class='xr-array-data'><pre>array([1, 2, 3, ..., 2, 3, 4])</pre></div></div></li><li class='xr-section-item'><input id='section-4f1546e8-d1df-47c9-b695-de0227064cef' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4f1546e8-d1df-47c9-b695-de0227064cef' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span 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'>1870-01-16T12:00:00 ... 2022-04-...</div><input id='attrs-193ee5c3-15c7-43e0-aedc-e3b82bd5c6b7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-193ee5c3-15c7-43e0-aedc-e3b82bd5c6b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91891e60-8f43-431d-a766-f7b02b59f0ee' class='xr-var-data-in' type='checkbox'><label for='data-91891e60-8f43-431d-a766-f7b02b59f0ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1870-01-16T12:00:00.000000000&#x27;, &#x27;1870-02-14T23:59:59.011230469&#x27;,\n",
       "       &#x27;1870-03-16T11:59:58.681640625&#x27;, ..., &#x27;2022-02-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2022-03-16T12:00:00.000000000&#x27;, &#x27;2022-04-16T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d2fc8c84-db60-49b4-b90e-3f859b0e0c32' class='xr-section-summary-in' type='checkbox'  ><label for='section-d2fc8c84-db60-49b4-b90e-3f859b0e0c32' 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-22560d36-6526-46a2-8282-58d8b312b516' class='xr-index-data-in' type='checkbox'/><label for='index-22560d36-6526-46a2-8282-58d8b312b516' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([          &#x27;1870-01-16 12:00:00&#x27;,\n",
       "               &#x27;1870-02-14 23:59:59.011230469&#x27;,\n",
       "               &#x27;1870-03-16 11:59:58.681640625&#x27;,\n",
       "               &#x27;1870-04-15 23:59:58.681640624&#x27;,\n",
       "                         &#x27;1870-05-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-06-16 00:00:00&#x27;,\n",
       "                         &#x27;1870-07-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-08-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-09-16 00:00:00&#x27;,\n",
       "                         &#x27;1870-10-16 12:00:00&#x27;,\n",
       "               ...\n",
       "                         &#x27;2021-07-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-08-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-09-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-10-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-11-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-12-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-01-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-02-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-03-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-04-16 12:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1828, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-07efa9ab-69ec-48e5-a9bc-a06a6306c926' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-07efa9ab-69ec-48e5-a9bc-a06a6306c926' 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 'month' (time: 1828)>\n",
       "array([1, 2, 3, ..., 2, 3, 4])\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# choose data in specific months\n",
    "\n",
    "sst.time.dt.month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;month&#x27; (time: 1828)&gt;\n",
       "array([ True, False, False, ..., False, False, False])\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'month'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1828</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-41767e4d-98c3-4d76-8ceb-8a66567b60ff' class='xr-array-in' type='checkbox' checked><label for='section-41767e4d-98c3-4d76-8ceb-8a66567b60ff' 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>True False False False False False ... False True False False False</span></div><div class='xr-array-data'><pre>array([ True, False, False, ..., False, False, False])</pre></div></div></li><li class='xr-section-item'><input id='section-3540a3e2-6098-495b-8d95-6daab7884048' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3540a3e2-6098-495b-8d95-6daab7884048' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span 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'>1870-01-16T12:00:00 ... 2022-04-...</div><input id='attrs-3c221416-f98f-4339-99e3-c4db6863bcb2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c221416-f98f-4339-99e3-c4db6863bcb2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5646dc61-abd3-431f-92f5-6ba0cb0b2182' class='xr-var-data-in' type='checkbox'><label for='data-5646dc61-abd3-431f-92f5-6ba0cb0b2182' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1870-01-16T12:00:00.000000000&#x27;, &#x27;1870-02-14T23:59:59.011230469&#x27;,\n",
       "       &#x27;1870-03-16T11:59:58.681640625&#x27;, ..., &#x27;2022-02-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2022-03-16T12:00:00.000000000&#x27;, &#x27;2022-04-16T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1fd7d432-5cbe-4d00-9e95-f89e09de4e68' class='xr-section-summary-in' type='checkbox'  ><label for='section-1fd7d432-5cbe-4d00-9e95-f89e09de4e68' 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-85d54d3c-ee03-4106-aa32-70ca63bef499' class='xr-index-data-in' type='checkbox'/><label for='index-85d54d3c-ee03-4106-aa32-70ca63bef499' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([          &#x27;1870-01-16 12:00:00&#x27;,\n",
       "               &#x27;1870-02-14 23:59:59.011230469&#x27;,\n",
       "               &#x27;1870-03-16 11:59:58.681640625&#x27;,\n",
       "               &#x27;1870-04-15 23:59:58.681640624&#x27;,\n",
       "                         &#x27;1870-05-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-06-16 00:00:00&#x27;,\n",
       "                         &#x27;1870-07-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-08-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-09-16 00:00:00&#x27;,\n",
       "                         &#x27;1870-10-16 12:00:00&#x27;,\n",
       "               ...\n",
       "                         &#x27;2021-07-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-08-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-09-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-10-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-11-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-12-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-01-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-02-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-03-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-04-16 12:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1828, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3c231864-5eae-4b5e-99aa-dfc8392a3cd9' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3c231864-5eae-4b5e-99aa-dfc8392a3cd9' 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 'month' (time: 1828)>\n",
       "array([ True, False, False, ..., False, False, False])\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label = (sst.time.dt.month == 1)\n",
    "label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
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       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-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",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".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-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-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-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (time: 153, lat: 90, lon: 180)&gt;\n",
       "[2478600 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-01-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean</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'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 153</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-61cd9374-a777-4a83-aac0-e0b602454daf' class='xr-array-in' type='checkbox' checked><label for='section-61cd9374-a777-4a83-aac0-e0b602454daf' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[2478600 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-c972b15f-95f0-4461-ad8d-156813c98b66' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c972b15f-95f0-4461-ad8d-156813c98b66' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1870-01-16T12:00:00 ... 2022-01-...</div><input id='attrs-6106e87a-3cc3-4ee0-90e6-7bb5ef3637ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6106e87a-3cc3-4ee0-90e6-7bb5ef3637ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-127c8d1b-3b9b-4db1-b9d6-71df6dd0101b' class='xr-var-data-in' type='checkbox'><label for='data-127c8d1b-3b9b-4db1-b9d6-71df6dd0101b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1870-01-16T12:00:00.000000000&#x27;, &#x27;1871-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1872-01-16T12:00:00.000000000&#x27;, &#x27;1873-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1874-01-16T12:00:00.000000000&#x27;, &#x27;1875-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1876-01-16T12:00:00.000000000&#x27;, &#x27;1877-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1878-01-16T12:00:00.000000000&#x27;, &#x27;1879-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1880-01-16T12:00:00.000000000&#x27;, &#x27;1881-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1882-01-16T12:00:00.000000000&#x27;, &#x27;1883-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1884-01-16T12:00:00.000000000&#x27;, &#x27;1885-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1886-01-16T12:00:00.000000000&#x27;, &#x27;1887-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1888-01-16T12:00:00.000000000&#x27;, &#x27;1889-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1890-01-16T12:00:00.000000000&#x27;, &#x27;1891-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1892-01-16T12:00:00.000000000&#x27;, &#x27;1893-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1894-01-16T12:00:00.000000000&#x27;, &#x27;1895-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1896-01-16T12:00:00.000000000&#x27;, &#x27;1897-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1898-01-16T12:00:00.000000000&#x27;, &#x27;1899-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1900-01-16T12:00:00.000000000&#x27;, &#x27;1901-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1902-01-16T12:00:00.000000000&#x27;, &#x27;1903-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1904-01-16T12:00:00.000000000&#x27;, &#x27;1905-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1906-01-16T12:00:00.000000000&#x27;, &#x27;1907-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1908-01-16T12:00:00.000000000&#x27;, &#x27;1909-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1910-01-16T12:00:00.000000000&#x27;, &#x27;1911-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1912-01-16T12:00:00.000000000&#x27;, &#x27;1913-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1914-01-16T12:00:00.000000000&#x27;, &#x27;1915-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1916-01-16T12:00:00.000000000&#x27;, &#x27;1917-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1918-01-16T12:00:00.000000000&#x27;, &#x27;1919-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1920-01-16T12:00:00.000000000&#x27;, &#x27;1921-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1922-01-16T12:00:00.000000000&#x27;, &#x27;1923-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1924-01-16T12:00:00.000000000&#x27;, &#x27;1925-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1926-01-16T12:00:00.000000000&#x27;, &#x27;1927-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1928-01-16T12:00:00.000000000&#x27;, &#x27;1929-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1930-01-16T12:00:00.000000000&#x27;, &#x27;1931-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1932-01-16T12:00:00.000000000&#x27;, &#x27;1933-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1934-01-16T12:00:00.000000000&#x27;, &#x27;1935-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1936-01-16T12:00:00.000000000&#x27;, &#x27;1937-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1938-01-16T12:00:00.000000000&#x27;, &#x27;1939-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1940-01-16T12:00:00.000000000&#x27;, &#x27;1941-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1942-01-16T12:00:00.000000000&#x27;, &#x27;1943-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1944-01-16T12:00:00.000000000&#x27;, &#x27;1945-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1946-01-16T12:00:00.000000000&#x27;, &#x27;1947-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1948-01-16T12:00:00.000000000&#x27;, &#x27;1949-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1950-01-16T12:00:00.000000000&#x27;, &#x27;1951-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1952-01-16T12:00:00.000000000&#x27;, &#x27;1953-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1954-01-16T12:00:00.000000000&#x27;, &#x27;1955-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1956-01-16T12:00:00.000000000&#x27;, &#x27;1957-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1958-01-16T12:00:00.000000000&#x27;, &#x27;1959-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1960-01-16T12:00:00.000000000&#x27;, &#x27;1961-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1962-01-16T12:00:00.000000000&#x27;, &#x27;1963-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1964-01-16T12:00:00.000000000&#x27;, &#x27;1965-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1966-01-16T12:00:00.000000000&#x27;, &#x27;1967-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1968-01-16T12:00:00.000000000&#x27;, &#x27;1969-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1970-01-16T12:00:00.000000000&#x27;, &#x27;1971-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1972-01-16T12:00:00.000000000&#x27;, &#x27;1973-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1974-01-16T12:00:00.000000000&#x27;, &#x27;1975-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1976-01-16T12:00:00.000000000&#x27;, &#x27;1977-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1978-01-16T12:00:00.000000000&#x27;, &#x27;1979-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1980-01-16T12:00:00.000000000&#x27;, &#x27;1981-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1982-01-16T12:00:00.000000000&#x27;, &#x27;1983-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1984-01-16T12:00:00.000000000&#x27;, &#x27;1985-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1986-01-16T12:00:00.000000000&#x27;, &#x27;1987-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1988-01-16T12:00:00.000000000&#x27;, &#x27;1989-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1990-01-16T12:00:00.000000000&#x27;, &#x27;1991-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1992-01-16T12:00:00.000000000&#x27;, &#x27;1993-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1994-01-16T12:00:00.000000000&#x27;, &#x27;1995-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1996-01-16T12:00:00.000000000&#x27;, &#x27;1997-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1998-01-16T12:00:00.000000000&#x27;, &#x27;1999-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2000-01-16T12:00:00.000000000&#x27;, &#x27;2001-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2002-01-16T12:00:00.000000000&#x27;, &#x27;2003-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2004-01-16T12:00:00.000000000&#x27;, &#x27;2005-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2006-01-16T12:00:00.000000000&#x27;, &#x27;2007-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2008-01-16T12:00:00.000000000&#x27;, &#x27;2009-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2010-01-16T12:00:00.000000000&#x27;, &#x27;2011-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2012-01-16T12:00:00.000000000&#x27;, &#x27;2013-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2014-01-16T12:00:00.000000000&#x27;, &#x27;2015-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2016-01-16T12:00:00.000000000&#x27;, &#x27;2017-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2018-01-16T12:00:00.000000000&#x27;, &#x27;2019-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2020-01-16T12:00:00.000000000&#x27;, &#x27;2021-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2022-01-16T12:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</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 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-3a99cf94-6724-4374-ad48-f5976406a1fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a99cf94-6724-4374-ad48-f5976406a1fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-36140622-57df-4522-b364-2995e7a77624' class='xr-var-data-in' type='checkbox'><label for='data-36140622-57df-4522-b364-2995e7a77624' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-5573ca51-8f97-4263-aded-d1dafda398a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5573ca51-8f97-4263-aded-d1dafda398a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2779cfd0-a6b8-4859-9c87-f7c5008edf55' class='xr-var-data-in' type='checkbox'><label for='data-2779cfd0-a6b8-4859-9c87-f7c5008edf55' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1afbce20-8c20-4e2d-a53b-7d39c21ff8d5' class='xr-section-summary-in' type='checkbox'  ><label for='section-1afbce20-8c20-4e2d-a53b-7d39c21ff8d5' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-38e718a2-9f8f-4b10-965c-d2ca826b4ef8' class='xr-index-data-in' type='checkbox'/><label for='index-38e718a2-9f8f-4b10-965c-d2ca826b4ef8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1870-01-16 12:00:00&#x27;, &#x27;1871-01-16 12:00:00&#x27;,\n",
       "               &#x27;1872-01-16 12:00:00&#x27;, &#x27;1873-01-16 12:00:00&#x27;,\n",
       "               &#x27;1874-01-16 12:00:00&#x27;, &#x27;1875-01-16 12:00:00&#x27;,\n",
       "               &#x27;1876-01-16 12:00:00&#x27;, &#x27;1877-01-16 12:00:00&#x27;,\n",
       "               &#x27;1878-01-16 12:00:00&#x27;, &#x27;1879-01-16 12:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2013-01-16 12:00:00&#x27;, &#x27;2014-01-16 12:00:00&#x27;,\n",
       "               &#x27;2015-01-16 12:00:00&#x27;, &#x27;2016-01-16 12:00:00&#x27;,\n",
       "               &#x27;2017-01-16 12:00:00&#x27;, &#x27;2018-01-16 12:00:00&#x27;,\n",
       "               &#x27;2019-01-16 12:00:00&#x27;, &#x27;2020-01-16 12:00:00&#x27;,\n",
       "               &#x27;2021-01-16 12:00:00&#x27;, &#x27;2022-01-16 12:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=153, freq=None))</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-3583db55-78ec-448f-af64-854aad958017' class='xr-index-data-in' type='checkbox'/><label for='index-3583db55-78ec-448f-af64-854aad958017' 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(Float64Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,\n",
       "               18.0,\n",
       "              ...\n",
       "              340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0,\n",
       "              358.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8878e807-c0cf-48f0-b7e1-2a9d3329a649' class='xr-index-data-in' type='checkbox'/><label for='index-8878e807-c0cf-48f0-b7e1-2a9d3329a649' 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(Float64Index([-89.0, -87.0, -85.0, -83.0, -81.0, -79.0, -77.0, -75.0, -73.0,\n",
       "              -71.0, -69.0, -67.0, -65.0, -63.0, -61.0, -59.0, -57.0, -55.0,\n",
       "              -53.0, -51.0, -49.0, -47.0, -45.0, -43.0, -41.0, -39.0, -37.0,\n",
       "              -35.0, -33.0, -31.0, -29.0, -27.0, -25.0, -23.0, -21.0, -19.0,\n",
       "              -17.0, -15.0, -13.0, -11.0,  -9.0,  -7.0,  -5.0,  -3.0,  -1.0,\n",
       "                1.0,   3.0,   5.0,   7.0,   9.0,  11.0,  13.0,  15.0,  17.0,\n",
       "               19.0,  21.0,  23.0,  25.0,  27.0,  29.0,  31.0,  33.0,  35.0,\n",
       "               37.0,  39.0,  41.0,  43.0,  45.0,  47.0,  49.0,  51.0,  53.0,\n",
       "               55.0,  57.0,  59.0,  61.0,  63.0,  65.0,  67.0,  69.0,  71.0,\n",
       "               73.0,  75.0,  77.0,  79.0,  81.0,  83.0,  85.0,  87.0,  89.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-90cdf115-ba8c-4555-8090-ade0952f5895' class='xr-section-summary-in' type='checkbox'  checked><label for='section-90cdf115-ba8c-4555-8090-ade0952f5895' 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>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>C</dd><dt><span>cell_methods :</span></dt><dd>time: lat: lon: mean</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (time: 153, lat: 90, lon: 180)>\n",
       "[2478600 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-01-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst[label]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
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       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (time: 153, lat: 90, lon: 180)&gt;\n",
       "[2478600 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-01-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean</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'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 153</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-3e0d3b66-f418-4c08-9dd2-f1d843820d24' class='xr-array-in' type='checkbox' checked><label for='section-3e0d3b66-f418-4c08-9dd2-f1d843820d24' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[2478600 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-b075d0ba-7095-475d-8428-d57d5b17f8fa' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b075d0ba-7095-475d-8428-d57d5b17f8fa' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1870-01-16T12:00:00 ... 2022-01-...</div><input id='attrs-28214b41-03ea-433f-bb2d-13f2f5670e61' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-28214b41-03ea-433f-bb2d-13f2f5670e61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f0c02d6-e6bf-41d9-bf04-60fa2d986fb8' class='xr-var-data-in' type='checkbox'><label for='data-8f0c02d6-e6bf-41d9-bf04-60fa2d986fb8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1870-01-16T12:00:00.000000000&#x27;, &#x27;1871-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1872-01-16T12:00:00.000000000&#x27;, &#x27;1873-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1874-01-16T12:00:00.000000000&#x27;, &#x27;1875-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1876-01-16T12:00:00.000000000&#x27;, &#x27;1877-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1878-01-16T12:00:00.000000000&#x27;, &#x27;1879-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1880-01-16T12:00:00.000000000&#x27;, &#x27;1881-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1882-01-16T12:00:00.000000000&#x27;, &#x27;1883-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1884-01-16T12:00:00.000000000&#x27;, &#x27;1885-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1886-01-16T12:00:00.000000000&#x27;, &#x27;1887-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1888-01-16T12:00:00.000000000&#x27;, &#x27;1889-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1890-01-16T12:00:00.000000000&#x27;, &#x27;1891-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1892-01-16T12:00:00.000000000&#x27;, &#x27;1893-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1894-01-16T12:00:00.000000000&#x27;, &#x27;1895-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1896-01-16T12:00:00.000000000&#x27;, &#x27;1897-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1898-01-16T12:00:00.000000000&#x27;, &#x27;1899-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1900-01-16T12:00:00.000000000&#x27;, &#x27;1901-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1902-01-16T12:00:00.000000000&#x27;, &#x27;1903-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1904-01-16T12:00:00.000000000&#x27;, &#x27;1905-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1906-01-16T12:00:00.000000000&#x27;, &#x27;1907-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1908-01-16T12:00:00.000000000&#x27;, &#x27;1909-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1910-01-16T12:00:00.000000000&#x27;, &#x27;1911-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1912-01-16T12:00:00.000000000&#x27;, &#x27;1913-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1914-01-16T12:00:00.000000000&#x27;, &#x27;1915-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1916-01-16T12:00:00.000000000&#x27;, &#x27;1917-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1918-01-16T12:00:00.000000000&#x27;, &#x27;1919-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1920-01-16T12:00:00.000000000&#x27;, &#x27;1921-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1922-01-16T12:00:00.000000000&#x27;, &#x27;1923-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1924-01-16T12:00:00.000000000&#x27;, &#x27;1925-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1926-01-16T12:00:00.000000000&#x27;, &#x27;1927-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1928-01-16T12:00:00.000000000&#x27;, &#x27;1929-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1930-01-16T12:00:00.000000000&#x27;, &#x27;1931-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1932-01-16T12:00:00.000000000&#x27;, &#x27;1933-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1934-01-16T12:00:00.000000000&#x27;, &#x27;1935-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1936-01-16T12:00:00.000000000&#x27;, &#x27;1937-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1938-01-16T12:00:00.000000000&#x27;, &#x27;1939-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1940-01-16T12:00:00.000000000&#x27;, &#x27;1941-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1942-01-16T12:00:00.000000000&#x27;, &#x27;1943-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1944-01-16T12:00:00.000000000&#x27;, &#x27;1945-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1946-01-16T12:00:00.000000000&#x27;, &#x27;1947-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1948-01-16T12:00:00.000000000&#x27;, &#x27;1949-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1950-01-16T12:00:00.000000000&#x27;, &#x27;1951-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1952-01-16T12:00:00.000000000&#x27;, &#x27;1953-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1954-01-16T12:00:00.000000000&#x27;, &#x27;1955-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1956-01-16T12:00:00.000000000&#x27;, &#x27;1957-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1958-01-16T12:00:00.000000000&#x27;, &#x27;1959-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1960-01-16T12:00:00.000000000&#x27;, &#x27;1961-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1962-01-16T12:00:00.000000000&#x27;, &#x27;1963-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1964-01-16T12:00:00.000000000&#x27;, &#x27;1965-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1966-01-16T12:00:00.000000000&#x27;, &#x27;1967-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1968-01-16T12:00:00.000000000&#x27;, &#x27;1969-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1970-01-16T12:00:00.000000000&#x27;, &#x27;1971-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1972-01-16T12:00:00.000000000&#x27;, &#x27;1973-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1974-01-16T12:00:00.000000000&#x27;, &#x27;1975-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1976-01-16T12:00:00.000000000&#x27;, &#x27;1977-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1978-01-16T12:00:00.000000000&#x27;, &#x27;1979-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1980-01-16T12:00:00.000000000&#x27;, &#x27;1981-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1982-01-16T12:00:00.000000000&#x27;, &#x27;1983-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1984-01-16T12:00:00.000000000&#x27;, &#x27;1985-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1986-01-16T12:00:00.000000000&#x27;, &#x27;1987-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1988-01-16T12:00:00.000000000&#x27;, &#x27;1989-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1990-01-16T12:00:00.000000000&#x27;, &#x27;1991-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1992-01-16T12:00:00.000000000&#x27;, &#x27;1993-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1994-01-16T12:00:00.000000000&#x27;, &#x27;1995-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1996-01-16T12:00:00.000000000&#x27;, &#x27;1997-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1998-01-16T12:00:00.000000000&#x27;, &#x27;1999-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2000-01-16T12:00:00.000000000&#x27;, &#x27;2001-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2002-01-16T12:00:00.000000000&#x27;, &#x27;2003-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2004-01-16T12:00:00.000000000&#x27;, &#x27;2005-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2006-01-16T12:00:00.000000000&#x27;, &#x27;2007-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2008-01-16T12:00:00.000000000&#x27;, &#x27;2009-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2010-01-16T12:00:00.000000000&#x27;, &#x27;2011-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2012-01-16T12:00:00.000000000&#x27;, &#x27;2013-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2014-01-16T12:00:00.000000000&#x27;, &#x27;2015-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2016-01-16T12:00:00.000000000&#x27;, &#x27;2017-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2018-01-16T12:00:00.000000000&#x27;, &#x27;2019-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2020-01-16T12:00:00.000000000&#x27;, &#x27;2021-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2022-01-16T12:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</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 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-cffd65f7-062e-406b-97cd-be76d0d040c7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cffd65f7-062e-406b-97cd-be76d0d040c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6569bb43-2b6b-4de3-bc04-d4317bf36a80' class='xr-var-data-in' type='checkbox'><label for='data-6569bb43-2b6b-4de3-bc04-d4317bf36a80' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-59a0702a-0fdc-4e8c-8791-99588e6ae392' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59a0702a-0fdc-4e8c-8791-99588e6ae392' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e5f74df-d30c-4f84-a791-11c538d0e0a2' class='xr-var-data-in' type='checkbox'><label for='data-9e5f74df-d30c-4f84-a791-11c538d0e0a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bb8562ba-416c-4809-93f1-7ea876bf1d30' class='xr-section-summary-in' type='checkbox'  ><label for='section-bb8562ba-416c-4809-93f1-7ea876bf1d30' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9d64122a-bfc2-4872-9ce9-7549071b62cc' class='xr-index-data-in' type='checkbox'/><label for='index-9d64122a-bfc2-4872-9ce9-7549071b62cc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1870-01-16 12:00:00&#x27;, &#x27;1871-01-16 12:00:00&#x27;,\n",
       "               &#x27;1872-01-16 12:00:00&#x27;, &#x27;1873-01-16 12:00:00&#x27;,\n",
       "               &#x27;1874-01-16 12:00:00&#x27;, &#x27;1875-01-16 12:00:00&#x27;,\n",
       "               &#x27;1876-01-16 12:00:00&#x27;, &#x27;1877-01-16 12:00:00&#x27;,\n",
       "               &#x27;1878-01-16 12:00:00&#x27;, &#x27;1879-01-16 12:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2013-01-16 12:00:00&#x27;, &#x27;2014-01-16 12:00:00&#x27;,\n",
       "               &#x27;2015-01-16 12:00:00&#x27;, &#x27;2016-01-16 12:00:00&#x27;,\n",
       "               &#x27;2017-01-16 12:00:00&#x27;, &#x27;2018-01-16 12:00:00&#x27;,\n",
       "               &#x27;2019-01-16 12:00:00&#x27;, &#x27;2020-01-16 12:00:00&#x27;,\n",
       "               &#x27;2021-01-16 12:00:00&#x27;, &#x27;2022-01-16 12:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=153, freq=None))</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-579e86d9-0649-4578-bb15-4699cd845026' class='xr-index-data-in' type='checkbox'/><label for='index-579e86d9-0649-4578-bb15-4699cd845026' 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(Float64Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,\n",
       "               18.0,\n",
       "              ...\n",
       "              340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0,\n",
       "              358.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-05ac529a-14cd-4fb3-a6b2-3f2648dd9206' class='xr-index-data-in' type='checkbox'/><label for='index-05ac529a-14cd-4fb3-a6b2-3f2648dd9206' 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(Float64Index([-89.0, -87.0, -85.0, -83.0, -81.0, -79.0, -77.0, -75.0, -73.0,\n",
       "              -71.0, -69.0, -67.0, -65.0, -63.0, -61.0, -59.0, -57.0, -55.0,\n",
       "              -53.0, -51.0, -49.0, -47.0, -45.0, -43.0, -41.0, -39.0, -37.0,\n",
       "              -35.0, -33.0, -31.0, -29.0, -27.0, -25.0, -23.0, -21.0, -19.0,\n",
       "              -17.0, -15.0, -13.0, -11.0,  -9.0,  -7.0,  -5.0,  -3.0,  -1.0,\n",
       "                1.0,   3.0,   5.0,   7.0,   9.0,  11.0,  13.0,  15.0,  17.0,\n",
       "               19.0,  21.0,  23.0,  25.0,  27.0,  29.0,  31.0,  33.0,  35.0,\n",
       "               37.0,  39.0,  41.0,  43.0,  45.0,  47.0,  49.0,  51.0,  53.0,\n",
       "               55.0,  57.0,  59.0,  61.0,  63.0,  65.0,  67.0,  69.0,  71.0,\n",
       "               73.0,  75.0,  77.0,  79.0,  81.0,  83.0,  85.0,  87.0,  89.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-39f36d3c-cb56-4d93-8c8f-7d7984905261' class='xr-section-summary-in' type='checkbox'  checked><label for='section-39f36d3c-cb56-4d93-8c8f-7d7984905261' 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>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>C</dd><dt><span>cell_methods :</span></dt><dd>time: lat: lon: mean</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (time: 153, lat: 90, lon: 180)>\n",
       "[2478600 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-01-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst.groupby(\"time.month\")[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (time: 459, lat: 90, lon: 180)&gt;\n",
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       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean</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'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 459</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-c561ae4d-d669-4e20-913c-f3efcf43bafc' class='xr-array-in' type='checkbox' checked><label for='section-c561ae4d-d669-4e20-913c-f3efcf43bafc' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[7435800 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-22f57a83-a08a-4041-8705-b822c5390e40' class='xr-section-summary-in' type='checkbox'  checked><label for='section-22f57a83-a08a-4041-8705-b822c5390e40' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1870-01-16T12:00:00 ... 2022-03-...</div><input id='attrs-1f5ef322-063d-4ec4-b1d1-837b848f9423' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f5ef322-063d-4ec4-b1d1-837b848f9423' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b975d2c-15c3-4b47-a819-e9a17a4ff666' class='xr-var-data-in' type='checkbox'><label for='data-6b975d2c-15c3-4b47-a819-e9a17a4ff666' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1870-01-16T12:00:00.000000000&#x27;, &#x27;1870-02-14T23:59:59.011230469&#x27;,\n",
       "       &#x27;1870-03-16T11:59:58.681640625&#x27;, ..., &#x27;2022-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2022-02-16T12:00:00.000000000&#x27;, &#x27;2022-03-16T12:00:00.000000000&#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'>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 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-572f85b1-549b-4c52-ba54-70547efa2bf4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-572f85b1-549b-4c52-ba54-70547efa2bf4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2742992-ee15-422b-a94d-c96a3b319d93' class='xr-var-data-in' type='checkbox'><label for='data-f2742992-ee15-422b-a94d-c96a3b319d93' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-ef292548-afa1-4b91-93d6-d3165154180c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ef292548-afa1-4b91-93d6-d3165154180c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aed80936-f832-4df8-bc27-ed65e7c4f26c' class='xr-var-data-in' type='checkbox'><label for='data-aed80936-f832-4df8-bc27-ed65e7c4f26c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ba6a9744-c8eb-48a7-8a28-d6f97e34802b' class='xr-section-summary-in' type='checkbox'  ><label for='section-ba6a9744-c8eb-48a7-8a28-d6f97e34802b' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-fcb0991f-c73b-44ed-9418-8e02cc994f2c' class='xr-index-data-in' type='checkbox'/><label for='index-fcb0991f-c73b-44ed-9418-8e02cc994f2c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([          &#x27;1870-01-16 12:00:00&#x27;,\n",
       "               &#x27;1870-02-14 23:59:59.011230469&#x27;,\n",
       "               &#x27;1870-03-16 11:59:58.681640625&#x27;,\n",
       "                         &#x27;1871-01-16 12:00:00&#x27;,\n",
       "                         &#x27;1871-02-15 00:00:00&#x27;,\n",
       "                         &#x27;1871-03-16 12:00:00&#x27;,\n",
       "                         &#x27;1872-01-16 12:00:00&#x27;,\n",
       "                         &#x27;1872-02-15 00:00:00&#x27;,\n",
       "                         &#x27;1872-03-16 12:00:00&#x27;,\n",
       "                         &#x27;1873-01-16 12:00:00&#x27;,\n",
       "               ...\n",
       "                         &#x27;2019-03-16 12:00:00&#x27;,\n",
       "                         &#x27;2020-01-16 12:00:00&#x27;,\n",
       "                         &#x27;2020-02-16 12:00:00&#x27;,\n",
       "                         &#x27;2020-03-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-01-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-02-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-03-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-01-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-02-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-03-16 12:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=459, freq=None))</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-403d3378-4412-4919-a941-ff383b43967f' class='xr-index-data-in' type='checkbox'/><label for='index-403d3378-4412-4919-a941-ff383b43967f' 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(Float64Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,\n",
       "               18.0,\n",
       "              ...\n",
       "              340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0,\n",
       "              358.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2ed8347c-587e-42f4-860b-d23090a69947' class='xr-index-data-in' type='checkbox'/><label for='index-2ed8347c-587e-42f4-860b-d23090a69947' 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(Float64Index([-89.0, -87.0, -85.0, -83.0, -81.0, -79.0, -77.0, -75.0, -73.0,\n",
       "              -71.0, -69.0, -67.0, -65.0, -63.0, -61.0, -59.0, -57.0, -55.0,\n",
       "              -53.0, -51.0, -49.0, -47.0, -45.0, -43.0, -41.0, -39.0, -37.0,\n",
       "              -35.0, -33.0, -31.0, -29.0, -27.0, -25.0, -23.0, -21.0, -19.0,\n",
       "              -17.0, -15.0, -13.0, -11.0,  -9.0,  -7.0,  -5.0,  -3.0,  -1.0,\n",
       "                1.0,   3.0,   5.0,   7.0,   9.0,  11.0,  13.0,  15.0,  17.0,\n",
       "               19.0,  21.0,  23.0,  25.0,  27.0,  29.0,  31.0,  33.0,  35.0,\n",
       "               37.0,  39.0,  41.0,  43.0,  45.0,  47.0,  49.0,  51.0,  53.0,\n",
       "               55.0,  57.0,  59.0,  61.0,  63.0,  65.0,  67.0,  69.0,  71.0,\n",
       "               73.0,  75.0,  77.0,  79.0,  81.0,  83.0,  85.0,  87.0,  89.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5d4614b5-9934-46ff-a2f7-37a6a79e8ade' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5d4614b5-9934-46ff-a2f7-37a6a79e8ade' 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>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>C</dd><dt><span>cell_methods :</span></dt><dd>time: lat: lon: mean</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (time: 459, lat: 90, lon: 180)>\n",
       "[7435800 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-03-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label = sst.time.dt.month.isin([1,2,3])\n",
    "label\n",
    "\n",
    "# label1 = sst.time.dt.month == 1\n",
    "# label2 = sst.time.dt.month == 2\n",
    "# labelall = label1 | label2 # &\n",
    "sst[label]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
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       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-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",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".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-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-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-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (time: 459, lat: 90, lon: 180)&gt;\n",
       "[7435800 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-03-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean</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'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 459</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-69ecb54b-1c41-4656-8df8-590806b07d2e' class='xr-array-in' type='checkbox' checked><label for='section-69ecb54b-1c41-4656-8df8-590806b07d2e' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[7435800 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-730de1f2-e173-426a-9f9d-bdefbe971a17' class='xr-section-summary-in' type='checkbox'  checked><label for='section-730de1f2-e173-426a-9f9d-bdefbe971a17' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1870-01-16T12:00:00 ... 2022-03-...</div><input id='attrs-14f0131a-456c-42b9-86d3-e44a32af8740' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14f0131a-456c-42b9-86d3-e44a32af8740' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2124e42a-257a-4584-82ca-24fbd92eb40d' class='xr-var-data-in' type='checkbox'><label for='data-2124e42a-257a-4584-82ca-24fbd92eb40d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1870-01-16T12:00:00.000000000&#x27;, &#x27;1870-02-14T23:59:59.011230469&#x27;,\n",
       "       &#x27;1870-03-16T11:59:58.681640625&#x27;, ..., &#x27;2022-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2022-02-16T12:00:00.000000000&#x27;, &#x27;2022-03-16T12:00:00.000000000&#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'>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 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-99407c9c-f210-4bff-8952-77ca68f3f404' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-99407c9c-f210-4bff-8952-77ca68f3f404' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adacd562-e9c2-4f19-8a26-fc7d85ece24e' class='xr-var-data-in' type='checkbox'><label for='data-adacd562-e9c2-4f19-8a26-fc7d85ece24e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-22df52c8-fb9f-4f16-996d-2d0e9f3a6ec8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22df52c8-fb9f-4f16-996d-2d0e9f3a6ec8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d67e56f-1b20-4604-ab5f-435a31f8ef94' class='xr-var-data-in' type='checkbox'><label for='data-8d67e56f-1b20-4604-ab5f-435a31f8ef94' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-300080bf-68c6-4a6a-9125-61268a6f4869' class='xr-section-summary-in' type='checkbox'  ><label for='section-300080bf-68c6-4a6a-9125-61268a6f4869' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-37a3280d-d2c9-40ab-8c4a-5f3331223f07' class='xr-index-data-in' type='checkbox'/><label for='index-37a3280d-d2c9-40ab-8c4a-5f3331223f07' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([          &#x27;1870-01-16 12:00:00&#x27;,\n",
       "               &#x27;1870-02-14 23:59:59.011230469&#x27;,\n",
       "               &#x27;1870-03-16 11:59:58.681640625&#x27;,\n",
       "                         &#x27;1871-01-16 12:00:00&#x27;,\n",
       "                         &#x27;1871-02-15 00:00:00&#x27;,\n",
       "                         &#x27;1871-03-16 12:00:00&#x27;,\n",
       "                         &#x27;1872-01-16 12:00:00&#x27;,\n",
       "                         &#x27;1872-02-15 00:00:00&#x27;,\n",
       "                         &#x27;1872-03-16 12:00:00&#x27;,\n",
       "                         &#x27;1873-01-16 12:00:00&#x27;,\n",
       "               ...\n",
       "                         &#x27;2019-03-16 12:00:00&#x27;,\n",
       "                         &#x27;2020-01-16 12:00:00&#x27;,\n",
       "                         &#x27;2020-02-16 12:00:00&#x27;,\n",
       "                         &#x27;2020-03-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-01-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-02-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-03-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-01-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-02-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-03-16 12:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=459, freq=None))</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-3fbc4231-8fac-4732-a1c7-55334205bbc1' class='xr-index-data-in' type='checkbox'/><label for='index-3fbc4231-8fac-4732-a1c7-55334205bbc1' 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(Float64Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,\n",
       "               18.0,\n",
       "              ...\n",
       "              340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0,\n",
       "              358.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d36ada1c-155f-4585-892a-640d8b9e6e2f' class='xr-index-data-in' type='checkbox'/><label for='index-d36ada1c-155f-4585-892a-640d8b9e6e2f' 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(Float64Index([-89.0, -87.0, -85.0, -83.0, -81.0, -79.0, -77.0, -75.0, -73.0,\n",
       "              -71.0, -69.0, -67.0, -65.0, -63.0, -61.0, -59.0, -57.0, -55.0,\n",
       "              -53.0, -51.0, -49.0, -47.0, -45.0, -43.0, -41.0, -39.0, -37.0,\n",
       "              -35.0, -33.0, -31.0, -29.0, -27.0, -25.0, -23.0, -21.0, -19.0,\n",
       "              -17.0, -15.0, -13.0, -11.0,  -9.0,  -7.0,  -5.0,  -3.0,  -1.0,\n",
       "                1.0,   3.0,   5.0,   7.0,   9.0,  11.0,  13.0,  15.0,  17.0,\n",
       "               19.0,  21.0,  23.0,  25.0,  27.0,  29.0,  31.0,  33.0,  35.0,\n",
       "               37.0,  39.0,  41.0,  43.0,  45.0,  47.0,  49.0,  51.0,  53.0,\n",
       "               55.0,  57.0,  59.0,  61.0,  63.0,  65.0,  67.0,  69.0,  71.0,\n",
       "               73.0,  75.0,  77.0,  79.0,  81.0,  83.0,  85.0,  87.0,  89.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-50880f37-7781-41f9-8b95-5e4cb63b4cad' class='xr-section-summary-in' type='checkbox'  checked><label for='section-50880f37-7781-41f9-8b95-5e4cb63b4cad' 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>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>C</dd><dt><span>cell_methods :</span></dt><dd>time: lat: lon: mean</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (time: 459, lat: 90, lon: 180)>\n",
       "[7435800 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-03-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst[label]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (time: 6, lat: 90, lon: 180)&gt;\n",
       "[97200 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1900-02-15 1900-03-16T12:00:00 ... 1902-04-16\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean</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'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 6</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-59fd2dac-9658-4749-9eb8-e00cf34e7da7' class='xr-array-in' type='checkbox' checked><label for='section-59fd2dac-9658-4749-9eb8-e00cf34e7da7' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[97200 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-e44649c3-e0dd-4818-ac8f-7c00d9ccd152' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e44649c3-e0dd-4818-ac8f-7c00d9ccd152' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1900-02-15 ... 1902-04-16</div><input id='attrs-035998ce-8a02-4f33-9448-a5811f2a8b68' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-035998ce-8a02-4f33-9448-a5811f2a8b68' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b39a4993-fd33-4786-acab-b278d963bb86' class='xr-var-data-in' type='checkbox'><label for='data-b39a4993-fd33-4786-acab-b278d963bb86' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1900-02-15T00:00:00.000000000&#x27;, &#x27;1900-03-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1900-04-16T00:00:00.000000000&#x27;, &#x27;1902-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;1902-03-16T12:00:00.000000000&#x27;, &#x27;1902-04-16T00:00:00.000000000&#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'>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 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-cc70fde2-e0b4-491c-b0b3-24eae55d9600' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc70fde2-e0b4-491c-b0b3-24eae55d9600' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3f0a31c-1a5f-4bf1-9720-4d3b43d47527' class='xr-var-data-in' type='checkbox'><label for='data-e3f0a31c-1a5f-4bf1-9720-4d3b43d47527' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-6c36d52d-edff-4bf9-890b-cc6a613a0db1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c36d52d-edff-4bf9-890b-cc6a613a0db1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6521adf2-1da8-428e-b094-cd1d7818c7d3' class='xr-var-data-in' type='checkbox'><label for='data-6521adf2-1da8-428e-b094-cd1d7818c7d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-16427faf-0bf5-4cd0-9fd8-044869894730' class='xr-section-summary-in' type='checkbox'  ><label for='section-16427faf-0bf5-4cd0-9fd8-044869894730' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4092b8a0-ad36-47a9-b61e-76c41edcffda' class='xr-index-data-in' type='checkbox'/><label for='index-4092b8a0-ad36-47a9-b61e-76c41edcffda' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1900-02-15 00:00:00&#x27;, &#x27;1900-03-16 12:00:00&#x27;,\n",
       "               &#x27;1900-04-16 00:00:00&#x27;, &#x27;1902-02-15 00:00:00&#x27;,\n",
       "               &#x27;1902-03-16 12:00:00&#x27;, &#x27;1902-04-16 00:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-48528147-795f-41da-aba8-3e6a93bd55f2' class='xr-index-data-in' type='checkbox'/><label for='index-48528147-795f-41da-aba8-3e6a93bd55f2' 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(Float64Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,\n",
       "               18.0,\n",
       "              ...\n",
       "              340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0,\n",
       "              358.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-39b99337-2768-482b-988e-6a9f0ad0efc5' class='xr-index-data-in' type='checkbox'/><label for='index-39b99337-2768-482b-988e-6a9f0ad0efc5' 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(Float64Index([-89.0, -87.0, -85.0, -83.0, -81.0, -79.0, -77.0, -75.0, -73.0,\n",
       "              -71.0, -69.0, -67.0, -65.0, -63.0, -61.0, -59.0, -57.0, -55.0,\n",
       "              -53.0, -51.0, -49.0, -47.0, -45.0, -43.0, -41.0, -39.0, -37.0,\n",
       "              -35.0, -33.0, -31.0, -29.0, -27.0, -25.0, -23.0, -21.0, -19.0,\n",
       "              -17.0, -15.0, -13.0, -11.0,  -9.0,  -7.0,  -5.0,  -3.0,  -1.0,\n",
       "                1.0,   3.0,   5.0,   7.0,   9.0,  11.0,  13.0,  15.0,  17.0,\n",
       "               19.0,  21.0,  23.0,  25.0,  27.0,  29.0,  31.0,  33.0,  35.0,\n",
       "               37.0,  39.0,  41.0,  43.0,  45.0,  47.0,  49.0,  51.0,  53.0,\n",
       "               55.0,  57.0,  59.0,  61.0,  63.0,  65.0,  67.0,  69.0,  71.0,\n",
       "               73.0,  75.0,  77.0,  79.0,  81.0,  83.0,  85.0,  87.0,  89.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9198b465-1f7f-4215-8ae3-0e07c685d9ec' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9198b465-1f7f-4215-8ae3-0e07c685d9ec' 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>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>C</dd><dt><span>cell_methods :</span></dt><dd>time: lat: lon: mean</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (time: 6, lat: 90, lon: 180)>\n",
       "[97200 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1900-02-15 1900-03-16T12:00:00 ... 1902-04-16\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "con1 = sst.time.dt.month.isin([2,3,4])\n",
    "con2 = sst.time.dt.year.isin([1900,1902])\n",
    "cona = con2 & con1 # \\ or\n",
    "sst[cona]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## plot plus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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rktxSVRe6+1s7MuHuGfpv6qXu/nWSX1fVI0muTzL2ABmyN3ck+ZuePNl3qap+muS6JP+6MyNetvbq43AipzYip2aTU7PJqdnk1KXZ8mPxdj917bEk11bV4aq6IsmtSc6sWXMmye0rr6RwU5JfdffPtnmuy8Gme1NV1yR5MMkn98BPOVbbdG+6+3B3v7O735nk75L81R4Ij2TYv6lvJ/lgVe2vqtcn+UCSZ3Z4zt0wZG+ey+QniKmqtyd5d5JzOzrl5WmvPg4ncmojcmo2OTWbnJpNTl2aLT8Wb+sdne6+UFV3JXk4k1eaON3dZ6vqzpXrJzN5JZJbkiwl+U0mTXb0Bu7N55K8NclXV34idKG7F3Zr5p0ycG/2pCF7093PVNX3kjyZ5NUk93X31JdqHJOB3zdfSHJ/VT2VyS3wu7v7pV0beodU1TeS3JzkqqpaTvL5JK9L9vbjcCKnNiKnZpNTs8mp2eTUxrYjq2pyZwwAAGA8tv0PhgIAAOw0RQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABidTYtOVZ2uqher6ukZ16uqvlxVS1X1ZFXdMP8xAWA6OQXANEPu6Nyf5OgG148luXbl7USSr136WAAw2P2RUwCssWnR6e5HkvxigyXHk3y9Jx5NcmVVvWNeAwLARuQUANPM43d0DiZ5ftXx8so5ALgcyCmAPWj/HD5GTTnXUxdWncjkaQN5wxve8L7rrrtuDp8egIv1+OOPv9TdB3Z7jm0mpwBeoy4lp+ZRdJaTXL3q+FCSF6Yt7O5TSU4lycLCQi8uLs7h0wNwsarq33d7hh0gpwBeoy4lp+bx1LUzSW5feVWbm5L8qrt/NoePCwDzIKcA9qBN7+hU1TeS3JzkqqpaTvL5JK9Lku4+meShJLckWUrymyR3bNewALCWnAJgmk2LTnfftsn1TvLpuU0EAFsgpwCYZh5PXQMAALisKDoAAMDoKDoAAMDoKDoAAMDoKDoAAMDoKDoAAMDoKDoAAMDoKDoAAMDoKDoAAMDoKDoAAMDoKDoAAMDoKDoAAMDoKDoAAMDoKDoAAMDoKDoAAMDoKDoAAMDoKDoAAMDoKDoAAMDoKDoAAMDoKDoAAMDoKDoAAMDoDCo6VXW0qp6tqqWqumfK9TdX1Xeq6kdVdbaq7pj/qAAwnZwCYK1Ni05V7Utyb5JjSY4kua2qjqxZ9ukkP+7u65PcnORvq+qKOc8KAOvIKQCmGXJH58YkS919rrtfTvJAkuNr1nSSN1VVJXljkl8kuTDXSQFgOjkFwDpDis7BJM+vOl5eObfaV5K8J8kLSZ5K8tnufnXtB6qqE1W1WFWL58+fv8iRAeC3yCkA1hlSdGrKuV5z/JEkTyT5vSR/mOQrVfW76/6j7lPdvdDdCwcOHNjiqAAwlZwCYJ0hRWc5ydWrjg9l8hOx1e5I8mBPLCX5aZLr5jMiAGxITgGwzpCi81iSa6vq8Movbt6a5MyaNc8l+XCSVNXbk7w7ybl5DgoAM8gpANbZv9mC7r5QVXcleTjJviSnu/tsVd25cv1kki8kub+qnsrkKQR3d/dL2zg3ACSRUwBMt2nRSZLufijJQ2vOnVz1/gtJ/mK+owHAMHIKgLUG/cFQAACA1xJFBwAAGB1FBwAAGB1FBwAAGB1FBwAAGB1FBwAAGB1FBwAAGB1FBwAAGB1FBwAAGB1FBwAAGB1FBwAAGB1FBwAAGB1FBwAAGB1FBwAAGB1FBwAAGB1FBwAAGB1FBwAAGB1FBwAAGB1FBwAAGB1FBwAAGJ1BRaeqjlbVs1W1VFX3zFhzc1U9UVVnq+oH8x0TAGaTUwCstX+zBVW1L8m9Sf48yXKSx6rqTHf/eNWaK5N8NcnR7n6uqt62TfMCwG+RUwBMM+SOzo1Jlrr7XHe/nOSBJMfXrPl4kge7+7kk6e4X5zsmAMwkpwBYZ0jROZjk+VXHyyvnVntXkrdU1fer6vGqun1eAwLAJuQUAOts+tS1JDXlXE/5OO9L8uEkv5Pkn6vq0e7+yW99oKoTSU4kyTXXXLP1aQFgPTkFwDpD7ugsJ7l61fGhJC9MWfO97v51d7+U5JEk16/9QN19qrsXunvhwIEDFzszAKwmpwBYZ0jReSzJtVV1uKquSHJrkjNr1nw7yQeran9VvT7JB5I8M99RAWAqOQXAOps+da27L1TVXUkeTrIvyenuPltVd65cP9ndz1TV95I8meTVJPd199PbOTgAJHIKgOmqe+3TmHfGwsJCLy4u7srnBmCiqh7v7oXdnuNyJKcAdt+l5NSgPxgKAADwWqLoAAAAo6PoAAAAo6PoAAAAo6PoAAAAo6PoAAAAo6PoAAAAo6PoAAAAo6PoAAAAo6PoAAAAo6PoAAAAo6PoAAAAo6PoAAAAo6PoAAAAo6PoAAAAo6PoAAAAo6PoAAAAo6PoAAAAo6PoAAAAo6PoAAAAo6PoAAAAozOo6FTV0ap6tqqWquqeDda9v6peqaqPzW9EANiYnAJgrU2LTlXtS3JvkmNJjiS5raqOzFj3xSQPz3tIAJhFTgEwzZA7OjcmWeruc939cpIHkhyfsu4zSb6Z5MU5zgcAm5FTAKwzpOgcTPL8quPllXP/o6oOJvlokpMbfaCqOlFVi1W1eP78+a3OCgDTyCkA1hlSdGrKuV5z/KUkd3f3Kxt9oO4+1d0L3b1w4MCBgSMCwIbkFADr7B+wZjnJ1auODyV5Yc2ahSQPVFWSXJXklqq60N3fmseQALABOQXAOkOKzmNJrq2qw0n+I8mtST6+ekF3H/7v96vq/iR/LzwA2CFyCoB1Ni063X2hqu7K5FVq9iU53d1nq+rOlesbPt8ZALaTnAJgmiF3dNLdDyV5aM25qcHR3X956WMBwHByCoC1Bv3BUAAAgNcSRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABgdRQcAABidQUWnqo5W1bNVtVRV90y5/omqenLl7YdVdf38RwWA6eQUAGttWnSqal+Se5McS3IkyW1VdWTNsp8m+dPufm+SLyQ5Ne9BAWAaOQXANEPu6NyYZKm7z3X3y0keSHJ89YLu/mF3/3Ll8NEkh+Y7JgDMJKcAWGdI0TmY5PlVx8sr52b5VJLvTrtQVSeqarGqFs+fPz98SgCYTU4BsM6QolNTzvXUhVUfyiRA7p52vbtPdfdCdy8cOHBg+JQAMJucAmCd/QPWLCe5etXxoSQvrF1UVe9Ncl+SY9398/mMBwCbklMArDPkjs5jSa6tqsNVdUWSW5OcWb2gqq5J8mCST3b3T+Y/JgDMJKcAWGfTOzrdfaGq7krycJJ9SU5399mqunPl+skkn0vy1iRfraokudDdC9s3NgBMyCkApqnuqU9j3nYLCwu9uLi4K58bgImqetz/8E8npwB236Xk1KA/GAoAAPBaougAAACjo+gAAACjo+gAAACjo+gAAACjo+gAAACjo+gAAACjo+gAAACjo+gAAACjo+gAAACjo+gAAACjo+gAAACjo+gAAACjo+gAAACjo+gAAACjo+gAAACjo+gAAACjo+gAAACjo+gAAACjo+gAAACjM6joVNXRqnq2qpaq6p4p16uqvrxy/cmqumH+owLAdHIKgLU2LTpVtS/JvUmOJTmS5LaqOrJm2bEk1668nUjytTnPCQBTySkAphlyR+fGJEvdfa67X07yQJLja9YcT/L1nng0yZVV9Y45zwoA08gpANYZUnQOJnl+1fHyyrmtrgGA7SCnAFhn/4A1NeVcX8SaVNWJTJ4ykCT/VVVPD/j8e9FVSV7a7SEuU/ZmNnszm72Z7d27PcAcyKmd59/UbPZmNnszm72Z7aJzakjRWU5y9arjQ0leuIg16e5TSU4lSVUtdvfClqbdI+zNbPZmNnszm72ZraoWd3uGOZBTO8zezGZvZrM3s9mb2S4lp4Y8de2xJNdW1eGquiLJrUnOrFlzJsntK69qc1OSX3X3zy52KADYAjkFwDqb3tHp7gtVdVeSh5PsS3K6u89W1Z0r108meSjJLUmWkvwmyR3bNzIA/C85BcA0Q566lu5+KJOQWH3u5Kr3O8mnt/i5T21x/V5ib2azN7PZm9nszWyj2Bs5tePszWz2ZjZ7M5u9me2i96Ymj/0AAADjMeR3dAAAAF5Ttr3oVNXRqnq2qpaq6p4p16uqvrxy/cmqumG7Z7pcDNibT6zsyZNV9cOqun435twNm+3NqnXvr6pXqupjOznfbhqyN1V1c1U9UVVnq+oHOz3jbhnwb+rNVfWdqvrRyt7sid/TqKrTVfXirJdK3suPw4mc2oicmk1OzSanZpNTs21LVnX3tr1l8kuh/5bk95NckeRHSY6sWXNLku9m8jcObkryL9s50+XyNnBv/ijJW1beP2Zvpq77x0yel/+x3Z77ctmbJFcm+XGSa1aO37bbc19Ge/PXSb648v6BJL9IcsVuz74De/MnSW5I8vSM63vycXgL3zd7cn/k1KXtzap1ckpObWVv9mROrXy9c8+q7b6jc2OSpe4+190vJ3kgyfE1a44n+XpPPJrkyqp6xzbPdTnYdG+6+4fd/cuVw0cz+bsPe8GQ75sk+UySbyZ5cSeH22VD9ubjSR7s7ueSpLv3yv4M2ZtO8qaqqiRvzCRALuzsmDuvux/J5GudZa8+DidyaiNyajY5NZucmk1ObWA7smq7i87BJM+vOl5eObfVNWO01a/7U5m02L1g072pqoNJPprkZPaWId8370rylqr6flU9XlW379h0u2vI3nwlyXsy+UORTyX5bHe/ujPjXdb26uNwIqc2Iqdmk1OzyanZ5NSl2fJj8aCXl74ENeXc2pd5G7JmjAZ/3VX1oUwC5I+3daLLx5C9+VKSu7v7lckPPfaMIXuzP8n7knw4ye8k+eeqerS7f7Ldw+2yIXvzkSRPJPmzJH+Q5B+q6p+6+z+3ebbL3V59HE7k1Ebk1GxyajY5NZucujRbfize7qKznOTqVceHMmmoW10zRoO+7qp6b5L7khzr7p/v0Gy7bcjeLCR5YCU8rkpyS1Vd6O5v7ciEu2fov6mXuvvXSX5dVY8kuT7J2ANkyN7ckeRvevJk36Wq+mmS65L8686MeNnaq4/DiZzaiJyaTU7NJqdmk1OXZsuPxdv91LXHklxbVYer6ooktyY5s2bNmSS3r7ySwk1JftXdP9vmuS4Hm+5NVV2T5MEkn9wDP+VYbdO96e7D3f3O7n5nkr9L8ld7IDySYf+mvp3kg1W1v6pen+QDSZ7Z4Tl3w5C9eS6TnyCmqt6e5N1Jzu3olJenvfo4nMipjcip2eTUbHJqNjl1abb8WLytd3S6+0JV3ZXk4UxeaeJ0d5+tqjtXrp/M5JVIbkmylOQ3mTTZ0Ru4N59L8tYkX135idCF7l7YrZl3ysC92ZOG7E13P1NV30vyZJJXk9zX3VNfqnFMBn7ffCHJ/VX1VCa3wO/u7pd2begdUlXfSHJzkquqajnJ55O8Ltnbj8OJnNqInJpNTs0mp2aTUxvbjqyqyZ0xAACA8dj2PxgKAACw0xQdAABgdBQdAABgdBQdAABgdBQdAABgdBQdAABgdBQdAABgdBQdAABgdP4/aCdhmqL8h54AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1008x432 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig = plt.figure(figsize=(14,6))\n",
    "\n",
    "ax1 = fig.add_subplot(2,2,1)\n",
    "ax2 = fig.add_subplot(2,2,2)\n",
    "ax3 = fig.add_subplot(2,2,3)\n",
    "ax4 = fig.add_subplot(2,2,4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
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       "\n",
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (season: 4, lat: 90, lon: 180)&gt;\n",
       "array([[[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-106.41506 ,  -45.389584,  -85.70994 , ...,  -57.9216  ,\n",
       "         -115.13296 ,  -49.748528],\n",
       "        [-126.5752  ,  -68.81893 ,  -66.63949 , ..., -133.6585  ,\n",
       "         -129.84439 , -124.94058 ],\n",
       "        [-533.0483  , -531.4139  , -529.23444 , ..., -537.9522  ,\n",
       "         -535.7727  , -530.32404 ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "...\n",
       "        [-223.0161  , -161.44649 , -163.62593 , ..., -362.5025  ,\n",
       "         -360.86783 , -409.9067  ],\n",
       "        [-313.46384 , -314.5536  , -254.07378 , ..., -203.94649 ,\n",
       "         -260.06735 , -310.73947 ],\n",
       "        [-556.4776  , -548.3046  , -545.03546 , ..., -554.29816 ,\n",
       "         -554.29816 , -552.1187  ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-367.3639  , -190.59764 , -130.94681 , ..., -194.97867 ,\n",
       "         -372.29037 , -430.29938 ],\n",
       "        [-194.98016 , -254.08376 , -374.48212 , ..., -316.47217 ,\n",
       "         -256.2733  , -315.37747 ],\n",
       "        [-444.5324  , -562.7415  , -563.2888  , ..., -563.2888  ,\n",
       "         -563.2888  , -442.89066 ]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "  * season   (season) object &#x27;DJF&#x27; &#x27;JJA&#x27; &#x27;MAM&#x27; &#x27;SON&#x27;\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean</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'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>season</span>: 4</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-2755b5e5-0fa4-4177-929d-cf0124641a02' class='xr-array-in' type='checkbox' checked><label for='section-2755b5e5-0fa4-4177-929d-cf0124641a02' 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>nan nan nan nan nan nan ... -564.9 -564.4 -445.1 -563.3 -563.3 -442.9</span></div><div class='xr-array-data'><pre>array([[[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-106.41506 ,  -45.389584,  -85.70994 , ...,  -57.9216  ,\n",
       "         -115.13296 ,  -49.748528],\n",
       "        [-126.5752  ,  -68.81893 ,  -66.63949 , ..., -133.6585  ,\n",
       "         -129.84439 , -124.94058 ],\n",
       "        [-533.0483  , -531.4139  , -529.23444 , ..., -537.9522  ,\n",
       "         -535.7727  , -530.32404 ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "...\n",
       "        [-223.0161  , -161.44649 , -163.62593 , ..., -362.5025  ,\n",
       "         -360.86783 , -409.9067  ],\n",
       "        [-313.46384 , -314.5536  , -254.07378 , ..., -203.94649 ,\n",
       "         -260.06735 , -310.73947 ],\n",
       "        [-556.4776  , -548.3046  , -545.03546 , ..., -554.29816 ,\n",
       "         -554.29816 , -552.1187  ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-367.3639  , -190.59764 , -130.94681 , ..., -194.97867 ,\n",
       "         -372.29037 , -430.29938 ],\n",
       "        [-194.98016 , -254.08376 , -374.48212 , ..., -316.47217 ,\n",
       "         -256.2733  , -315.37747 ],\n",
       "        [-444.5324  , -562.7415  , -563.2888  , ..., -563.2888  ,\n",
       "         -563.2888  , -442.89066 ]]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-8ec6ccec-57a5-4315-8042-477837c7f59e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8ec6ccec-57a5-4315-8042-477837c7f59e' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-9ae2784d-3394-47ac-9d9d-e4eadcb28fdd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ae2784d-3394-47ac-9d9d-e4eadcb28fdd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cbc2abf1-7814-4001-9b44-2248af40dd0a' class='xr-var-data-in' type='checkbox'><label for='data-cbc2abf1-7814-4001-9b44-2248af40dd0a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-13d65630-3776-4671-baf8-35478fec137c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-13d65630-3776-4671-baf8-35478fec137c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5eefc62d-1a0c-47e6-b572-a96d160942fa' class='xr-var-data-in' type='checkbox'><label for='data-5eefc62d-1a0c-47e6-b572-a96d160942fa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>season</span></div><div class='xr-var-dims'>(season)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;DJF&#x27; &#x27;JJA&#x27; &#x27;MAM&#x27; &#x27;SON&#x27;</div><input id='attrs-2f927ef3-881a-44a6-88e9-03a4543f3055' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2f927ef3-881a-44a6-88e9-03a4543f3055' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44f0dfee-e33f-4e43-a842-4538242d0094' class='xr-var-data-in' type='checkbox'><label for='data-44f0dfee-e33f-4e43-a842-4538242d0094' 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([&#x27;DJF&#x27;, &#x27;JJA&#x27;, &#x27;MAM&#x27;, &#x27;SON&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-42466438-06c2-4292-95fc-35afe0bcd458' class='xr-section-summary-in' type='checkbox'  ><label for='section-42466438-06c2-4292-95fc-35afe0bcd458' 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>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-fde76307-543b-49ae-a6b1-b948f712ace9' class='xr-index-data-in' type='checkbox'/><label for='index-fde76307-543b-49ae-a6b1-b948f712ace9' 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(Float64Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,\n",
       "               18.0,\n",
       "              ...\n",
       "              340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0,\n",
       "              358.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-564d78ba-7ad0-4f92-a9ab-b41c71ee5131' class='xr-index-data-in' type='checkbox'/><label for='index-564d78ba-7ad0-4f92-a9ab-b41c71ee5131' 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(Float64Index([-89.0, -87.0, -85.0, -83.0, -81.0, -79.0, -77.0, -75.0, -73.0,\n",
       "              -71.0, -69.0, -67.0, -65.0, -63.0, -61.0, -59.0, -57.0, -55.0,\n",
       "              -53.0, -51.0, -49.0, -47.0, -45.0, -43.0, -41.0, -39.0, -37.0,\n",
       "              -35.0, -33.0, -31.0, -29.0, -27.0, -25.0, -23.0, -21.0, -19.0,\n",
       "              -17.0, -15.0, -13.0, -11.0,  -9.0,  -7.0,  -5.0,  -3.0,  -1.0,\n",
       "                1.0,   3.0,   5.0,   7.0,   9.0,  11.0,  13.0,  15.0,  17.0,\n",
       "               19.0,  21.0,  23.0,  25.0,  27.0,  29.0,  31.0,  33.0,  35.0,\n",
       "               37.0,  39.0,  41.0,  43.0,  45.0,  47.0,  49.0,  51.0,  53.0,\n",
       "               55.0,  57.0,  59.0,  61.0,  63.0,  65.0,  67.0,  69.0,  71.0,\n",
       "               73.0,  75.0,  77.0,  79.0,  81.0,  83.0,  85.0,  87.0,  89.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>season</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-89d862b7-a963-47b2-9206-5973a08c432c' class='xr-index-data-in' type='checkbox'/><label for='index-89d862b7-a963-47b2-9206-5973a08c432c' 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([&#x27;DJF&#x27;, &#x27;JJA&#x27;, &#x27;MAM&#x27;, &#x27;SON&#x27;], dtype=&#x27;object&#x27;, name=&#x27;season&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-31e60622-c74d-499c-88c1-a2c385e6e77d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-31e60622-c74d-499c-88c1-a2c385e6e77d' 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>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>C</dd><dt><span>cell_methods :</span></dt><dd>time: lat: lon: mean</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (season: 4, lat: 90, lon: 180)>\n",
       "array([[[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-106.41506 ,  -45.389584,  -85.70994 , ...,  -57.9216  ,\n",
       "         -115.13296 ,  -49.748528],\n",
       "        [-126.5752  ,  -68.81893 ,  -66.63949 , ..., -133.6585  ,\n",
       "         -129.84439 , -124.94058 ],\n",
       "        [-533.0483  , -531.4139  , -529.23444 , ..., -537.9522  ,\n",
       "         -535.7727  , -530.32404 ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "...\n",
       "        [-223.0161  , -161.44649 , -163.62593 , ..., -362.5025  ,\n",
       "         -360.86783 , -409.9067  ],\n",
       "        [-313.46384 , -314.5536  , -254.07378 , ..., -203.94649 ,\n",
       "         -260.06735 , -310.73947 ],\n",
       "        [-556.4776  , -548.3046  , -545.03546 , ..., -554.29816 ,\n",
       "         -554.29816 , -552.1187  ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-367.3639  , -190.59764 , -130.94681 , ..., -194.97867 ,\n",
       "         -372.29037 , -430.29938 ],\n",
       "        [-194.98016 , -254.08376 , -374.48212 , ..., -316.47217 ,\n",
       "         -256.2733  , -315.37747 ],\n",
       "        [-444.5324  , -562.7415  , -563.2888  , ..., -563.2888  ,\n",
       "         -563.2888  , -442.89066 ]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "  * season   (season) object 'DJF' 'JJA' 'MAM' 'SON'\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sstsm = sst.groupby(\"time.season\").mean()\n",
    "sstsm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "sstdjf = sstsm.loc['DJF']\n",
    "sstjja = sstsm.loc['JJA']\n",
    "sstson = sstsm.loc[\"SON\"]\n",
    "sstmam = sstsm.loc['MAM']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1008x432 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "x = sst.lon\n",
    "y = sst.lat\n",
    "fig = plt.figure(figsize=(14,6))\n",
    "# =====================================\n",
    "ax1 = fig.add_subplot(2,2,1)\n",
    "m = ax1.contourf(x,y,sstmam,levels=np.linspace(0,35,15),cmap=\"RdBu_r\",extend=\"both\")\n",
    "plt.colorbar(m)\n",
    "\n",
    "# 补全剩下四张图\n",
    "ax2 = fig.add_subplot(2,2,2)\n",
    "\n",
    "ax3 = fig.add_subplot(2,2,3)\n",
    "ax4 = fig.add_subplot(2,2,4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 作业\n",
    "\n",
    "计算12个月的气候态平均海温并在一个fig上使用循环画出。"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "sacpy",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.16"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}