climate-dt/climate-dt-earthkit-fe-story-nudging.ipynb

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    "## Polytope Climate-DT Time Series example notebook for story nudging\n",
    "\n",
    "This notebook shows how to use earthkit-data and earthkit-plots to pull destination-earth data from LUMI and plot it using earthkit-plots.\n",
    "\n",
    "Before running the notebook you need to set up your credentials. See the main readme of this repository for different ways to do this or use the following cells to authenticate.\n",
    "\n",
    "You will need to generate your credentials using the desp-authentication.py script.\n",
    "\n",
    "This can be run as follows:"
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    "%%capture cap\n",
    "%run ../desp-authentication.py"
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    "This will generate a token that can then be used by earthkit and polytope."
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    "output_1 = cap.stdout.split('}\\n')\n",
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    "# Requirements\n",
    "To run this notebook install the following:\n",
    "* pip install earthkit-data\n",
    "* pip install earthkit-plots\n",
    "* pip install earthkit-regrid  (Optional for spectral variables)\n",
    "* pip install cf-units         (Optional for unit conversion in maps)\n",
    "\n",
    "If you do not have eccodes installed please install eccodes using conda as it is a dependency of earthkit, or install earthkit via conda\n",
    "\n",
    "* conda install eccodes -c conda-forge\n",
    "* conda install earthkit-data -c conda-forge"
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    "# This request matches multiple parameter of the climate DT\n",
    " \n",
    "import earthkit.data\n",
    "\n",
    "LOCATION = ((38, -9.5))\n",
    "\n",
    "\n",
    "request = {\n",
    "     \"activity\": \"story-nudging\",\n",
    "     \"class\": \"d1\",\n",
    "     \"dataset\": \"climate-dt\",\n",
    "     \"experiment\": \"cont\",\n",
    "     \"generation\": \"1\",\n",
    "     \"levtype\": \"sfc\",\n",
    "     \"date\": \"20180205/to/20180220\",\n",
    "     \"model\": \"ifs-fesom\",\n",
    "     \"expver\": \"0001\",\n",
    "     \"param\": \"165\",\n",
    "     \"realization\": \"1\",\n",
    "     \"resolution\": \"high\",\n",
    "     \"stream\": \"clte\",\n",
    "     \"type\": \"fc\",\n",
    "     \"time\": \"0000\",\n",
    "     \"feature\": {\n",
    "         \"type\": \"timeseries\",\n",
    "         \"points\": [[38, -9.5]],\n",
    "         \"time_axis\": \"date\",\n",
    "     }\n",
    " }\n",
    "\n",
    "ds = earthkit.data.from_source(\"polytope\", \"destination-earth\", request, stream=False, address='polytope.lumi.apps.dte.destination-earth.eu')\n"
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    "def location_to_string(location):\n",
    "    \"\"\"\n",
    "    Converts latitude and longitude to a string representation with degrees\n",
    "    and N/S/E/W.\n",
    "    \"\"\"\n",
    "    (lat, lon) = location\n",
    "    lat_dir = \"N\" if lat >= 0 else \"S\"\n",
    "    lon_dir = \"E\" if lon >= 0 else \"W\"\n",
    "    return f\"{abs(lat):.2f}°{lat_dir}, {abs(lon):.2f}°{lon_dir}\""
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       "    number:         0\n",
       "    Forecast date:  2018-02-20 00:00:00Z</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-8088114b-6bc6-4847-a772-e07b86868d7f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8088114b-6bc6-4847-a772-e07b86868d7f' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x</span>: 1</li><li><span class='xr-has-index'>y</span>: 1</li><li><span class='xr-has-index'>z</span>: 1</li><li><span class='xr-has-index'>number</span>: 1</li><li><span class='xr-has-index'>datetime</span>: 1</li><li><span class='xr-has-index'>t</span>: 16</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-be49dce7-5e83-49b2-941e-cbb1034f7c70' class='xr-section-summary-in' type='checkbox'  checked><label for='section-be49dce7-5e83-49b2-941e-cbb1034f7c70' class='xr-section-summary' >Coordinates: <span>(6)</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'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>38.02</div><input id='attrs-c5d97e98-084b-4108-989a-8815031e6470' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c5d97e98-084b-4108-989a-8815031e6470' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a3ad215-a071-4701-be43-179a5ff144ef' class='xr-var-data-in' type='checkbox'><label for='data-7a3ad215-a071-4701-be43-179a5ff144ef' 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([38.016284])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>350.5</div><input id='attrs-5ce39d76-42e4-45c0-9f69-e003171ae4d0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5ce39d76-42e4-45c0-9f69-e003171ae4d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e5a222d6-a17d-4504-8d77-dc454e5f7668' class='xr-var-data-in' type='checkbox'><label for='data-e5a222d6-a17d-4504-8d77-dc454e5f7668' 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([350.507812])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>z</span></div><div class='xr-var-dims'>(z)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-381152e3-1406-4424-8ed5-b5ef3a946c30' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-381152e3-1406-4424-8ed5-b5ef3a946c30' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98588c02-5ef0-4540-9aa4-5230d23c35cf' class='xr-var-data-in' type='checkbox'><label for='data-98588c02-5ef0-4540-9aa4-5230d23c35cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>number</span></div><div class='xr-var-dims'>(number)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-86957f10-eea7-4d25-ae96-a67f978f0744' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-86957f10-eea7-4d25-ae96-a67f978f0744' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15fa6511-d638-49f7-87eb-18cac34c45e7' class='xr-var-data-in' type='checkbox'><label for='data-15fa6511-d638-49f7-87eb-18cac34c45e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>datetime</span></div><div class='xr-var-dims'>(datetime)</div><div class='xr-var-dtype'>&lt;U20</div><div class='xr-var-preview xr-preview'>&#x27;2018-02-20 00:00:00Z&#x27;</div><input id='attrs-8337212a-6b81-48fe-a7e6-8c5695a38c8c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8337212a-6b81-48fe-a7e6-8c5695a38c8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da827049-fd42-4629-b225-d37364a926da' class='xr-var-data-in' type='checkbox'><label for='data-da827049-fd42-4629-b225-d37364a926da' 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;2018-02-20 00:00:00Z&#x27;], dtype=&#x27;&lt;U20&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>t</span></div><div class='xr-var-dims'>(t)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2018-02-05 ... 2018-02-20</div><input id='attrs-b332cff2-3e57-4b17-91fa-cd8011107eab' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b332cff2-3e57-4b17-91fa-cd8011107eab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ab74f32-9a35-4601-b062-4589b5d66f10' class='xr-var-data-in' type='checkbox'><label for='data-5ab74f32-9a35-4601-b062-4589b5d66f10' 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;2018-02-05T00:00:00.000000000&#x27;, &#x27;2018-02-06T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-02-07T00:00:00.000000000&#x27;, &#x27;2018-02-08T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-02-09T00:00:00.000000000&#x27;, &#x27;2018-02-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-02-11T00:00:00.000000000&#x27;, &#x27;2018-02-12T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-02-13T00:00:00.000000000&#x27;, &#x27;2018-02-14T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-02-15T00:00:00.000000000&#x27;, &#x27;2018-02-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-02-17T00:00:00.000000000&#x27;, &#x27;2018-02-18T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-02-19T00:00:00.000000000&#x27;, &#x27;2018-02-20T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-72188794-85d7-4068-81cc-c11c62bb036f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-72188794-85d7-4068-81cc-c11c62bb036f' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>10u</span></div><div class='xr-var-dims'>(x, y, z, number, datetime, t)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.035 -1.31 ... -3.496 -1.723</div><input id='attrs-b2414600-028a-4418-8c49-4fcd407ca183' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2414600-028a-4418-8c49-4fcd407ca183' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a8dd41d-59c4-4cc5-986d-31574c2ae575' class='xr-var-data-in' type='checkbox'><label for='data-0a8dd41d-59c4-4cc5-986d-31574c2ae575' 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>type :</span></dt><dd>Parameter</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>10u</dd></dl></div><div class='xr-var-data'><pre>array([[[[[[-1.03497505, -1.31013298, -3.71728134, -7.0200386 ,\n",
       "             0.06177711, -1.03588676, -1.34597397,  8.12549019,\n",
       "             2.32795143,  5.28248215,  3.29925919,  2.3224659 ,\n",
       "             2.56562805, -1.3319397 , -3.49638557, -1.72289085]]]]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-84047180-b48f-4bac-8ed2-fd0cb91b4055' class='xr-section-summary-in' type='checkbox'  ><label for='section-84047180-b48f-4bac-8ed2-fd0cb91b4055' class='xr-section-summary' >Indexes: <span>(6)</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>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cac9738c-e6f4-4d52-9859-183e0ef021da' class='xr-index-data-in' type='checkbox'/><label for='index-cac9738c-e6f4-4d52-9859-183e0ef021da' 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([38.016284446058], dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7016d5d2-0d22-4324-997e-4790bdf50d57' class='xr-index-data-in' type='checkbox'/><label for='index-7016d5d2-0d22-4324-997e-4790bdf50d57' 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([350.5078125], dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>z</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8d735964-133a-4809-a718-46624ddcda9a' class='xr-index-data-in' type='checkbox'/><label for='index-8d735964-133a-4809-a718-46624ddcda9a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0], dtype=&#x27;int64&#x27;, name=&#x27;z&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>number</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b412aff1-ba46-49f5-aee1-b400277bf989' class='xr-index-data-in' type='checkbox'/><label for='index-b412aff1-ba46-49f5-aee1-b400277bf989' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0], dtype=&#x27;int64&#x27;, name=&#x27;number&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>datetime</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-001de2c8-f2cb-42c0-abf8-82c840a26a3a' class='xr-index-data-in' type='checkbox'/><label for='index-001de2c8-f2cb-42c0-abf8-82c840a26a3a' 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;2018-02-20 00:00:00Z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;datetime&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>t</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7f0127f5-5092-4869-98aa-c32977bef894' class='xr-index-data-in' type='checkbox'/><label for='index-7f0127f5-5092-4869-98aa-c32977bef894' 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;2018-02-05&#x27;, &#x27;2018-02-06&#x27;, &#x27;2018-02-07&#x27;, &#x27;2018-02-08&#x27;,\n",
       "               &#x27;2018-02-09&#x27;, &#x27;2018-02-10&#x27;, &#x27;2018-02-11&#x27;, &#x27;2018-02-12&#x27;,\n",
       "               &#x27;2018-02-13&#x27;, &#x27;2018-02-14&#x27;, &#x27;2018-02-15&#x27;, &#x27;2018-02-16&#x27;,\n",
       "               &#x27;2018-02-17&#x27;, &#x27;2018-02-18&#x27;, &#x27;2018-02-19&#x27;, &#x27;2018-02-20&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;t&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2c68ca34-82a9-4495-a407-5f093620304e' class='xr-section-summary-in' type='checkbox'  ><label for='section-2c68ca34-82a9-4495-a407-5f093620304e' class='xr-section-summary' >Attributes: <span>(14)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>activity :</span></dt><dd>story-nudging</dd><dt><span>class :</span></dt><dd>d1</dd><dt><span>dataset :</span></dt><dd>climate-dt</dd><dt><span>experiment :</span></dt><dd>cont</dd><dt><span>expver :</span></dt><dd>0001</dd><dt><span>generation :</span></dt><dd>1</dd><dt><span>levtype :</span></dt><dd>sfc</dd><dt><span>model :</span></dt><dd>ifs-fesom</dd><dt><span>realization :</span></dt><dd>1</dd><dt><span>resolution :</span></dt><dd>high</dd><dt><span>stream :</span></dt><dd>clte</dd><dt><span>type :</span></dt><dd>fc</dd><dt><span>number :</span></dt><dd>0</dd><dt><span>Forecast date :</span></dt><dd>2018-02-20 00:00:00Z</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 368B\n",
       "Dimensions:   (x: 1, y: 1, z: 1, number: 1, datetime: 1, t: 16)\n",
       "Coordinates:\n",
       "  * x         (x) float64 8B 38.02\n",
       "  * y         (y) float64 8B 350.5\n",
       "  * z         (z) int64 8B 0\n",
       "  * number    (number) int64 8B 0\n",
       "  * datetime  (datetime) <U20 80B '2018-02-20 00:00:00Z'\n",
       "  * t         (t) datetime64[ns] 128B 2018-02-05 2018-02-06 ... 2018-02-20\n",
       "Data variables:\n",
       "    10u       (x, y, z, number, datetime, t) float64 128B -1.035 ... -1.723\n",
       "Attributes: (12/14)\n",
       "    activity:       story-nudging\n",
       "    class:          d1\n",
       "    dataset:        climate-dt\n",
       "    experiment:     cont\n",
       "    expver:         0001\n",
       "    generation:     1\n",
       "    ...             ...\n",
       "    realization:    1\n",
       "    resolution:     high\n",
       "    stream:         clte\n",
       "    type:           fc\n",
       "    number:         0\n",
       "    Forecast date:  2018-02-20 00:00:00Z"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "da = ds.to_xarray()\n",
    "da"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f12d8515",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from earthkit.plots.interactive import Chart\n",
    "\n",
    "TIME_FREQUENCY = \"1d\"\n",
    "QUANTILES = [0, 0.1, 0.25, 0.5, 0.75, 0.9, 1]\n",
    "\n",
    "chart = Chart()\n",
    "chart.title(f\"ECMWF ensemble meteogram at {location_to_string(LOCATION)}\")\n",
    "#chart.box(ds, time_frequency=TIME_FREQUENCY, quantiles=QUANTILES)\n",
    "chart.line(ds, line_color='grey', time_frequency=TIME_FREQUENCY)\n",
    "chart.show(\"png\")  # Replace with chart.show() in an interactive session!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ae75ea72",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "polytope_venv",
   "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": "3.11.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}