calculate_jet_latitude_and_speed.ipynb

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    "# Example usage: jet latitude and speed statistics\n",
    "Entire notebook takes 2 minutes to run on Intel i7-10750. 10 seconds for first part.\n",
    "\n",
    "## Index\n",
    "[Woollings et al. 2010](#Woollings-et-al.-2010)  \n",
    "[Barnes & Polvani 2013](#Barnes-&-Polvani-2013)  \n",
    "[Grise & Polvani 2014](#Grise-&-Polvani-2014)  \n",
    "[Barnes & Polvani 2015](#Barnes-&-Polvani-2015)  \n",
    "[Barnes & Simpson 2017](#Barnes-&-Simpson-2017)  \n",
    "[Bracegirdle et al. 2018](#Bracegirdle-et-al.-2018)  \n",
    "[Ceppi et al. 2018](#Ceppi-et-al.-2018)  \n",
    "[Kerr et al. 2020](#Kerr-et-al.-2020)  \n",
    "[Compare all](#Compare-all)\n",
    "\n",
    "preprint describing the package: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-661/"
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      "xarray version: 2023.3.0\n",
      "jsmetrics version: 0.2.0\n"
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   "source": [
    "## For calculation of jet latitude and speed statistics\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "import jsmetrics\n",
    "print(\"xarray version:\", xr.__version__) ## tested on 0.1.3\n",
    "print(\"jsmetrics version:\", jsmetrics.__version__) ## tested on 2023.3.0\n",
    "\n",
    "## For plotting\n",
    "import matplotlib.pyplot as plt"
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    "## load in and format ERA5 data"
   ]
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   "source": [
    "ua = xr.open_dataset('data/era5_u_wind_JF21.nc')\n"
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    "## this is necessary because jsmetrics currently only accept standardised names as input. This may change in the future\n",
    "ua = ua.rename({'longitude':'lon', 'latitude':'lat', 'level':'plev', 'u':'ua'})\n"
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (lon: 360, lat: 91, plev: 6, time: 59)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 0.0 1.0 2.0 3.0 4.0 ... 355.0 356.0 357.0 358.0 359.0\n",
       "  * lat      (lat) float32 90.0 89.0 88.0 87.0 86.0 85.0 ... 4.0 3.0 2.0 1.0 0.0\n",
       "  * plev     (plev) int32 100 250 300 500 700 850\n",
       "  * time     (time) datetime64[ns] 2021-01-01 2021-01-02 ... 2021-02-28\n",
       "Data variables:\n",
       "    ua       (time, plev, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmw...</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-20f76510-6f7d-45da-9474-3d2bf9063d89' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-20f76510-6f7d-45da-9474-3d2bf9063d89' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 360</li><li><span class='xr-has-index'>lat</span>: 91</li><li><span class='xr-has-index'>plev</span>: 6</li><li><span class='xr-has-index'>time</span>: 59</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-210af9d9-b7cd-49b9-8118-8349e03b4f88' class='xr-section-summary-in' type='checkbox'  checked><label for='section-210af9d9-b7cd-49b9-8118-8349e03b4f88' 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'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 1.0 2.0 ... 357.0 358.0 359.0</div><input id='attrs-b948efa0-b882-49bb-9c3f-0fc5900501c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b948efa0-b882-49bb-9c3f-0fc5900501c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7976134-76cd-41f0-8866-af9fc04c2bd0' class='xr-var-data-in' type='checkbox'><label for='data-d7976134-76cd-41f0-8866-af9fc04c2bd0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   1.,   2., ..., 357., 358., 359.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>90.0 89.0 88.0 87.0 ... 2.0 1.0 0.0</div><input id='attrs-5c9d6998-c0ed-4585-9bc3-267269ef58d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c9d6998-c0ed-4585-9bc3-267269ef58d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb74a76f-9303-4fae-bd9b-2f1660ffb40a' class='xr-var-data-in' type='checkbox'><label for='data-fb74a76f-9303-4fae-bd9b-2f1660ffb40a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77.,\n",
       "       76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63.,\n",
       "       62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49.,\n",
       "       48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35.,\n",
       "       34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21.,\n",
       "       20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10.,  9.,  8.,  7.,\n",
       "        6.,  5.,  4.,  3.,  2.,  1.,  0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>plev</span></div><div class='xr-var-dims'>(plev)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>100 250 300 500 700 850</div><input id='attrs-b386732e-04f0-4111-875a-e73bfb03c818' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b386732e-04f0-4111-875a-e73bfb03c818' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a9462bdc-7109-4892-bc74-064c16cf7de3' class='xr-var-data-in' type='checkbox'><label for='data-a9462bdc-7109-4892-bc74-064c16cf7de3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>millibars</dd><dt><span>long_name :</span></dt><dd>pressure_level</dd></dl></div><div class='xr-var-data'><pre>array([100, 250, 300, 500, 700, 850], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-01-01 ... 2021-02-28</div><input id='attrs-2b9620da-48e0-484b-a17e-445425f4adbe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b9620da-48e0-484b-a17e-445425f4adbe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6a9f730-4da2-4ba2-95bf-be353c91b951' class='xr-var-data-in' type='checkbox'><label for='data-c6a9f730-4da2-4ba2-95bf-be353c91b951' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T00:00:00.000000000&#x27;, &#x27;2021-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-03T00:00:00.000000000&#x27;, &#x27;2021-01-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-05T00:00:00.000000000&#x27;, &#x27;2021-01-06T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-07T00:00:00.000000000&#x27;, &#x27;2021-01-08T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-09T00:00:00.000000000&#x27;, &#x27;2021-01-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-11T00:00:00.000000000&#x27;, &#x27;2021-01-12T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-13T00:00:00.000000000&#x27;, &#x27;2021-01-14T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-15T00:00:00.000000000&#x27;, &#x27;2021-01-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-17T00:00:00.000000000&#x27;, &#x27;2021-01-18T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-19T00:00:00.000000000&#x27;, &#x27;2021-01-20T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-21T00:00:00.000000000&#x27;, &#x27;2021-01-22T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-23T00:00:00.000000000&#x27;, &#x27;2021-01-24T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-25T00:00:00.000000000&#x27;, &#x27;2021-01-26T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-27T00:00:00.000000000&#x27;, &#x27;2021-01-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-29T00:00:00.000000000&#x27;, &#x27;2021-01-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-31T00:00:00.000000000&#x27;, &#x27;2021-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-02T00:00:00.000000000&#x27;, &#x27;2021-02-03T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-04T00:00:00.000000000&#x27;, &#x27;2021-02-05T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-06T00:00:00.000000000&#x27;, &#x27;2021-02-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-08T00:00:00.000000000&#x27;, &#x27;2021-02-09T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-10T00:00:00.000000000&#x27;, &#x27;2021-02-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-12T00:00:00.000000000&#x27;, &#x27;2021-02-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-14T00:00:00.000000000&#x27;, &#x27;2021-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-16T00:00:00.000000000&#x27;, &#x27;2021-02-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-18T00:00:00.000000000&#x27;, &#x27;2021-02-19T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-20T00:00:00.000000000&#x27;, &#x27;2021-02-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-22T00:00:00.000000000&#x27;, &#x27;2021-02-23T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-24T00:00:00.000000000&#x27;, &#x27;2021-02-25T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-26T00:00:00.000000000&#x27;, &#x27;2021-02-27T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-28T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-621efd93-0787-49b0-95a7-05a08dc93ae9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-621efd93-0787-49b0-95a7-05a08dc93ae9' 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>ua</span></div><div class='xr-var-dims'>(time, plev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-42900cfc-17e6-471f-8e3f-3f516bb687e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42900cfc-17e6-471f-8e3f-3f516bb687e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-76b82d34-e7dc-4534-96cc-8466cad75bae' class='xr-var-data-in' type='checkbox'><label for='data-76b82d34-e7dc-4534-96cc-8466cad75bae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>U component of wind</dd><dt><span>standard_name :</span></dt><dd>eastward_wind</dd></dl></div><div class='xr-var-data'><pre>[11597040 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5d7da3d1-c608-4118-929d-7d8e34080c4e' class='xr-section-summary-in' type='checkbox'  ><label for='section-5d7da3d1-c608-4118-929d-7d8e34080c4e' class='xr-section-summary' >Indexes: <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-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2146a8c8-87ce-43a2-be36-264108da3536' class='xr-index-data-in' type='checkbox'/><label for='index-2146a8c8-87ce-43a2-be36-264108da3536' 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,   1.0,   2.0,   3.0,   4.0,   5.0,   6.0,   7.0,   8.0,\n",
       "                9.0,\n",
       "              ...\n",
       "              350.0, 351.0, 352.0, 353.0, 354.0, 355.0, 356.0, 357.0, 358.0,\n",
       "              359.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=360))</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-58e1957e-a212-4d73-8a80-cbe3f7a8350e' class='xr-index-data-in' type='checkbox'/><label for='index-58e1957e-a212-4d73-8a80-cbe3f7a8350e' 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([90.0, 89.0, 88.0, 87.0, 86.0, 85.0, 84.0, 83.0, 82.0, 81.0, 80.0,\n",
       "              79.0, 78.0, 77.0, 76.0, 75.0, 74.0, 73.0, 72.0, 71.0, 70.0, 69.0,\n",
       "              68.0, 67.0, 66.0, 65.0, 64.0, 63.0, 62.0, 61.0, 60.0, 59.0, 58.0,\n",
       "              57.0, 56.0, 55.0, 54.0, 53.0, 52.0, 51.0, 50.0, 49.0, 48.0, 47.0,\n",
       "              46.0, 45.0, 44.0, 43.0, 42.0, 41.0, 40.0, 39.0, 38.0, 37.0, 36.0,\n",
       "              35.0, 34.0, 33.0, 32.0, 31.0, 30.0, 29.0, 28.0, 27.0, 26.0, 25.0,\n",
       "              24.0, 23.0, 22.0, 21.0, 20.0, 19.0, 18.0, 17.0, 16.0, 15.0, 14.0,\n",
       "              13.0, 12.0, 11.0, 10.0,  9.0,  8.0,  7.0,  6.0,  5.0,  4.0,  3.0,\n",
       "               2.0,  1.0,  0.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>plev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8702387e-2613-4ca4-a466-f2c20723f558' class='xr-index-data-in' type='checkbox'/><label for='index-8702387e-2613-4ca4-a466-f2c20723f558' 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([100, 250, 300, 500, 700, 850], dtype=&#x27;int64&#x27;, name=&#x27;plev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-60c96707-e517-400f-ba3a-70e00dc7066b' class='xr-index-data-in' type='checkbox'/><label for='index-60c96707-e517-400f-ba3a-70e00dc7066b' 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;2021-01-01&#x27;, &#x27;2021-01-02&#x27;, &#x27;2021-01-03&#x27;, &#x27;2021-01-04&#x27;,\n",
       "               &#x27;2021-01-05&#x27;, &#x27;2021-01-06&#x27;, &#x27;2021-01-07&#x27;, &#x27;2021-01-08&#x27;,\n",
       "               &#x27;2021-01-09&#x27;, &#x27;2021-01-10&#x27;, &#x27;2021-01-11&#x27;, &#x27;2021-01-12&#x27;,\n",
       "               &#x27;2021-01-13&#x27;, &#x27;2021-01-14&#x27;, &#x27;2021-01-15&#x27;, &#x27;2021-01-16&#x27;,\n",
       "               &#x27;2021-01-17&#x27;, &#x27;2021-01-18&#x27;, &#x27;2021-01-19&#x27;, &#x27;2021-01-20&#x27;,\n",
       "               &#x27;2021-01-21&#x27;, &#x27;2021-01-22&#x27;, &#x27;2021-01-23&#x27;, &#x27;2021-01-24&#x27;,\n",
       "               &#x27;2021-01-25&#x27;, &#x27;2021-01-26&#x27;, &#x27;2021-01-27&#x27;, &#x27;2021-01-28&#x27;,\n",
       "               &#x27;2021-01-29&#x27;, &#x27;2021-01-30&#x27;, &#x27;2021-01-31&#x27;, &#x27;2021-02-01&#x27;,\n",
       "               &#x27;2021-02-02&#x27;, &#x27;2021-02-03&#x27;, &#x27;2021-02-04&#x27;, &#x27;2021-02-05&#x27;,\n",
       "               &#x27;2021-02-06&#x27;, &#x27;2021-02-07&#x27;, &#x27;2021-02-08&#x27;, &#x27;2021-02-09&#x27;,\n",
       "               &#x27;2021-02-10&#x27;, &#x27;2021-02-11&#x27;, &#x27;2021-02-12&#x27;, &#x27;2021-02-13&#x27;,\n",
       "               &#x27;2021-02-14&#x27;, &#x27;2021-02-15&#x27;, &#x27;2021-02-16&#x27;, &#x27;2021-02-17&#x27;,\n",
       "               &#x27;2021-02-18&#x27;, &#x27;2021-02-19&#x27;, &#x27;2021-02-20&#x27;, &#x27;2021-02-21&#x27;,\n",
       "               &#x27;2021-02-22&#x27;, &#x27;2021-02-23&#x27;, &#x27;2021-02-24&#x27;, &#x27;2021-02-25&#x27;,\n",
       "               &#x27;2021-02-26&#x27;, &#x27;2021-02-27&#x27;, &#x27;2021-02-28&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7890506d-3cda-40aa-9305-653e09b3e723' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7890506d-3cda-40aa-9305-653e09b3e723' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmwf/mars-client/bin/grib_to_netcdf -S param -o /cache/data6/adaptor.mars.internal-1645789868.3978655-14915-10-d5b8d9d1-2766-4630-b88f-1f6a21a2a0a4.nc /cache/tmp/d5b8d9d1-2766-4630-b88f-1f6a21a2a0a4-adaptor.mars.internal-1645789330.2418482-14915-17-tmp.grib</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lon: 360, lat: 91, plev: 6, time: 59)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 0.0 1.0 2.0 3.0 4.0 ... 355.0 356.0 357.0 358.0 359.0\n",
       "  * lat      (lat) float32 90.0 89.0 88.0 87.0 86.0 85.0 ... 4.0 3.0 2.0 1.0 0.0\n",
       "  * plev     (plev) int32 100 250 300 500 700 850\n",
       "  * time     (time) datetime64[ns] 2021-01-01 2021-01-02 ... 2021-02-28\n",
       "Data variables:\n",
       "    ua       (time, plev, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmw..."
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ua"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d45318a6-8496-444c-b7bf-639bd52681b4",
   "metadata": {},
   "source": [
    "## Calculate metrics"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00b27108-243b-4e10-ade7-aa373baf2ad3",
   "metadata": {},
   "source": [
    "### Woollings et al. 2010"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e7f42a68-cbca-40bf-a029-92d9e7165262",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 224 ms, sys: 4.65 ms, total: 228 ms\n",
      "Wall time: 228 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "## In this example we look at only north atlantic and reduce filter freq and window size for Woollings et al. 2010\n",
    "# This takes ~300 milliseconds on Intel i7-10750\n",
    "w10 = jsmetrics.jet_statistics.woollings_et_al_2010(\\\n",
    "                    ua.sel(lon=slice(300, 360), lat=slice(70, 20),\\\n",
    "                           plev=slice(700, 850)),\\\n",
    "                    filter_freq=4, window_size=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d2aa52da-7351-4a9a-ac71-4c822a77d0e6",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:       (lat: 51, time: 59, season: 1)\n",
       "Coordinates:\n",
       "  * lat           (lat) float32 20.0 21.0 22.0 23.0 24.0 ... 67.0 68.0 69.0 70.0\n",
       "  * time          (time) datetime64[ns] 2021-01-01 2021-01-02 ... 2021-02-28\n",
       "Dimensions without coordinates: season\n",
       "Data variables:\n",
       "    ua            (time, lat) float32 6.265 7.045 7.302 ... 8.566 6.973 6.54\n",
       "    jet_lat       (time) float64 nan nan nan nan nan nan ... nan nan nan nan nan\n",
       "    jet_speed     (time) float64 nan nan nan nan nan nan ... nan nan nan nan nan\n",
       "    ff_jet_lat    (season) float64 43.44\n",
       "    ff_jet_speed  (season) float64 16.58</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-4c78f596-f3d6-418b-833c-1166527e3391' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4c78f596-f3d6-418b-833c-1166527e3391' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 51</li><li><span class='xr-has-index'>time</span>: 59</li><li><span>season</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f0a22868-3e60-4ceb-a527-955d7d1fdd26' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f0a22868-3e60-4ceb-a527-955d7d1fdd26' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 21.0 22.0 ... 68.0 69.0 70.0</div><input id='attrs-ba840d3e-b329-43cd-8169-67d83cfec80d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba840d3e-b329-43cd-8169-67d83cfec80d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d63a760d-243a-4ae0-894e-6d38f53cf3cf' class='xr-var-data-in' type='checkbox'><label for='data-d63a760d-243a-4ae0-894e-6d38f53cf3cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([20., 21., 22., 23., 24., 25., 26., 27., 28., 29., 30., 31., 32., 33.,\n",
       "       34., 35., 36., 37., 38., 39., 40., 41., 42., 43., 44., 45., 46., 47.,\n",
       "       48., 49., 50., 51., 52., 53., 54., 55., 56., 57., 58., 59., 60., 61.,\n",
       "       62., 63., 64., 65., 66., 67., 68., 69., 70.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-01-01 ... 2021-02-28</div><input id='attrs-ad69fae6-2ea5-4d9b-b31c-af26c97ce487' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad69fae6-2ea5-4d9b-b31c-af26c97ce487' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a9fa8746-3b04-4015-a48f-b4b3957c1eda' class='xr-var-data-in' type='checkbox'><label for='data-a9fa8746-3b04-4015-a48f-b4b3957c1eda' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T00:00:00.000000000&#x27;, &#x27;2021-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-03T00:00:00.000000000&#x27;, &#x27;2021-01-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-05T00:00:00.000000000&#x27;, &#x27;2021-01-06T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-07T00:00:00.000000000&#x27;, &#x27;2021-01-08T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-09T00:00:00.000000000&#x27;, &#x27;2021-01-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-11T00:00:00.000000000&#x27;, &#x27;2021-01-12T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-13T00:00:00.000000000&#x27;, &#x27;2021-01-14T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-15T00:00:00.000000000&#x27;, &#x27;2021-01-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-17T00:00:00.000000000&#x27;, &#x27;2021-01-18T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-19T00:00:00.000000000&#x27;, &#x27;2021-01-20T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-21T00:00:00.000000000&#x27;, &#x27;2021-01-22T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-23T00:00:00.000000000&#x27;, &#x27;2021-01-24T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-25T00:00:00.000000000&#x27;, &#x27;2021-01-26T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-27T00:00:00.000000000&#x27;, &#x27;2021-01-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-29T00:00:00.000000000&#x27;, &#x27;2021-01-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-31T00:00:00.000000000&#x27;, &#x27;2021-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-02T00:00:00.000000000&#x27;, &#x27;2021-02-03T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-04T00:00:00.000000000&#x27;, &#x27;2021-02-05T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-06T00:00:00.000000000&#x27;, &#x27;2021-02-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-08T00:00:00.000000000&#x27;, &#x27;2021-02-09T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-10T00:00:00.000000000&#x27;, &#x27;2021-02-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-12T00:00:00.000000000&#x27;, &#x27;2021-02-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-14T00:00:00.000000000&#x27;, &#x27;2021-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-16T00:00:00.000000000&#x27;, &#x27;2021-02-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-18T00:00:00.000000000&#x27;, &#x27;2021-02-19T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-20T00:00:00.000000000&#x27;, &#x27;2021-02-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-22T00:00:00.000000000&#x27;, &#x27;2021-02-23T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-24T00:00:00.000000000&#x27;, &#x27;2021-02-25T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-26T00:00:00.000000000&#x27;, &#x27;2021-02-27T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-28T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ee5f505f-ba28-4188-b08a-444e0840043f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ee5f505f-ba28-4188-b08a-444e0840043f' class='xr-section-summary' >Data variables: <span>(5)</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>ua</span></div><div class='xr-var-dims'>(time, lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>6.265 7.045 7.302 ... 6.973 6.54</div><input id='attrs-991d11e2-7dbe-4b5b-b3fc-771f9ebe81be' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-991d11e2-7dbe-4b5b-b3fc-771f9ebe81be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cdb7d847-0085-4cc8-a9ef-50ea82e1ab15' class='xr-var-data-in' type='checkbox'><label for='data-cdb7d847-0085-4cc8-a9ef-50ea82e1ab15' 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([[ 6.2652006 ,  7.0453367 ,  7.302196  , ...,  5.559306  ,\n",
       "         4.6819177 ,  4.043632  ],\n",
       "       [ 5.5461125 ,  5.8807316 ,  6.3271756 , ..., -0.13401814,\n",
       "         0.7061901 ,  1.538102  ],\n",
       "       [ 3.7577698 ,  4.7055955 ,  5.771403  , ...,  1.6448634 ,\n",
       "         2.3673513 ,  2.6989038 ],\n",
       "       ...,\n",
       "       [-8.831663  , -9.54671   , -9.428634  , ..., -3.8537421 ,\n",
       "        -2.0335917 , -1.1536362 ],\n",
       "       [-8.88149   , -8.137274  , -7.1395497 , ...,  0.7687113 ,\n",
       "        -0.9561358 , -2.920037  ],\n",
       "       [-4.2007704 , -3.6809652 , -2.86441   , ...,  8.565528  ,\n",
       "         6.972737  ,  6.5404606 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jet_lat</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b3eda971-5928-4120-b8d0-19b3814ac115' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b3eda971-5928-4120-b8d0-19b3814ac115' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e947def0-42a9-4e10-bb71-0e49e0224df0' class='xr-var-data-in' type='checkbox'><label for='data-e947def0-42a9-4e10-bb71-0e49e0224df0' 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([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 53., 53., 47.,\n",
       "       46., 54., 58., 59., 38., 38., 41., 42., 42., 41., 39., 39., 38.,\n",
       "       37., 40., 40., 39., 39., 39., 42., 41., 41., 50., 47., 44., 44.,\n",
       "       41., 40., 40., 41., 42., 42., 43., 45., 45., 44., nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jet_speed</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-649a1b84-0a32-427b-9602-0097f5b861c1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-649a1b84-0a32-427b-9602-0097f5b861c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d290a7ea-562f-4c2c-a3cb-375957d8f8ab' class='xr-var-data-in' type='checkbox'><label for='data-d290a7ea-562f-4c2c-a3cb-375957d8f8ab' 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([        nan,         nan,         nan,         nan,         nan,\n",
       "               nan,         nan,         nan,         nan,         nan,\n",
       "       10.48405125, 12.1740213 , 12.73824259, 11.02142468, 10.86352043,\n",
       "       13.12665216, 13.63765945, 12.27172918, 15.4588792 , 17.6730636 ,\n",
       "       19.0657645 , 19.38308593, 18.88915735, 18.67627855, 18.24502587,\n",
       "       16.12958022, 14.17510359, 13.72902061, 15.83876088, 18.66735713,\n",
       "       19.95686143, 18.86048995, 16.9181733 , 13.60541028,  9.91212763,\n",
       "       10.08462658, 12.95226702, 17.07738746, 20.4283791 , 22.2959086 ,\n",
       "       23.24448563, 22.72983579, 21.5508454 , 20.15420566, 17.61165236,\n",
       "       15.8924005 , 18.36626434, 21.32328972, 21.45457413,         nan,\n",
       "               nan,         nan,         nan,         nan,         nan,\n",
       "               nan,         nan,         nan,         nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ff_jet_lat</span></div><div class='xr-var-dims'>(season)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>43.44</div><input id='attrs-f048f5ac-de59-4dee-a5d4-7e66a4c51244' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f048f5ac-de59-4dee-a5d4-7e66a4c51244' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2b7582a-bdf3-4ec8-9136-2d490129743f' class='xr-var-data-in' type='checkbox'><label for='data-a2b7582a-bdf3-4ec8-9136-2d490129743f' 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([43.43589744])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ff_jet_speed</span></div><div class='xr-var-dims'>(season)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>16.58</div><input id='attrs-6e2c3feb-f037-4640-9694-64d3b95f3e53' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6e2c3feb-f037-4640-9694-64d3b95f3e53' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88ec6bdc-3304-4f7f-95ee-1e924b0c6a10' class='xr-var-data-in' type='checkbox'><label for='data-88ec6bdc-3304-4f7f-95ee-1e924b0c6a10' 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([16.58121957])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f3cfae2f-52f9-4d3f-a7dd-de8b19ac0f87' class='xr-section-summary-in' type='checkbox'  ><label for='section-f3cfae2f-52f9-4d3f-a7dd-de8b19ac0f87' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ea7dd1b2-6789-47aa-bef2-630306adb78b' class='xr-index-data-in' type='checkbox'/><label for='index-ea7dd1b2-6789-47aa-bef2-630306adb78b' 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([20.0, 21.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0,\n",
       "              31.0, 32.0, 33.0, 34.0, 35.0, 36.0, 37.0, 38.0, 39.0, 40.0, 41.0,\n",
       "              42.0, 43.0, 44.0, 45.0, 46.0, 47.0, 48.0, 49.0, 50.0, 51.0, 52.0,\n",
       "              53.0, 54.0, 55.0, 56.0, 57.0, 58.0, 59.0, 60.0, 61.0, 62.0, 63.0,\n",
       "              64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6049e657-4587-493b-af76-43c42e70967c' class='xr-index-data-in' type='checkbox'/><label for='index-6049e657-4587-493b-af76-43c42e70967c' 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;2021-01-01&#x27;, &#x27;2021-01-02&#x27;, &#x27;2021-01-03&#x27;, &#x27;2021-01-04&#x27;,\n",
       "               &#x27;2021-01-05&#x27;, &#x27;2021-01-06&#x27;, &#x27;2021-01-07&#x27;, &#x27;2021-01-08&#x27;,\n",
       "               &#x27;2021-01-09&#x27;, &#x27;2021-01-10&#x27;, &#x27;2021-01-11&#x27;, &#x27;2021-01-12&#x27;,\n",
       "               &#x27;2021-01-13&#x27;, &#x27;2021-01-14&#x27;, &#x27;2021-01-15&#x27;, &#x27;2021-01-16&#x27;,\n",
       "               &#x27;2021-01-17&#x27;, &#x27;2021-01-18&#x27;, &#x27;2021-01-19&#x27;, &#x27;2021-01-20&#x27;,\n",
       "               &#x27;2021-01-21&#x27;, &#x27;2021-01-22&#x27;, &#x27;2021-01-23&#x27;, &#x27;2021-01-24&#x27;,\n",
       "               &#x27;2021-01-25&#x27;, &#x27;2021-01-26&#x27;, &#x27;2021-01-27&#x27;, &#x27;2021-01-28&#x27;,\n",
       "               &#x27;2021-01-29&#x27;, &#x27;2021-01-30&#x27;, &#x27;2021-01-31&#x27;, &#x27;2021-02-01&#x27;,\n",
       "               &#x27;2021-02-02&#x27;, &#x27;2021-02-03&#x27;, &#x27;2021-02-04&#x27;, &#x27;2021-02-05&#x27;,\n",
       "               &#x27;2021-02-06&#x27;, &#x27;2021-02-07&#x27;, &#x27;2021-02-08&#x27;, &#x27;2021-02-09&#x27;,\n",
       "               &#x27;2021-02-10&#x27;, &#x27;2021-02-11&#x27;, &#x27;2021-02-12&#x27;, &#x27;2021-02-13&#x27;,\n",
       "               &#x27;2021-02-14&#x27;, &#x27;2021-02-15&#x27;, &#x27;2021-02-16&#x27;, &#x27;2021-02-17&#x27;,\n",
       "               &#x27;2021-02-18&#x27;, &#x27;2021-02-19&#x27;, &#x27;2021-02-20&#x27;, &#x27;2021-02-21&#x27;,\n",
       "               &#x27;2021-02-22&#x27;, &#x27;2021-02-23&#x27;, &#x27;2021-02-24&#x27;, &#x27;2021-02-25&#x27;,\n",
       "               &#x27;2021-02-26&#x27;, &#x27;2021-02-27&#x27;, &#x27;2021-02-28&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d5d23ce8-ad06-4bef-a24b-4af75321e899' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d5d23ce8-ad06-4bef-a24b-4af75321e899' 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.Dataset>\n",
       "Dimensions:       (lat: 51, time: 59, season: 1)\n",
       "Coordinates:\n",
       "  * lat           (lat) float32 20.0 21.0 22.0 23.0 24.0 ... 67.0 68.0 69.0 70.0\n",
       "  * time          (time) datetime64[ns] 2021-01-01 2021-01-02 ... 2021-02-28\n",
       "Dimensions without coordinates: season\n",
       "Data variables:\n",
       "    ua            (time, lat) float32 6.265 7.045 7.302 ... 8.566 6.973 6.54\n",
       "    jet_lat       (time) float64 nan nan nan nan nan nan ... nan nan nan nan nan\n",
       "    jet_speed     (time) float64 nan nan nan nan nan nan ... nan nan nan nan nan\n",
       "    ff_jet_lat    (season) float64 43.44\n",
       "    ff_jet_speed  (season) float64 16.58"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "07676aef-b6ea-4860-ae5c-be82e571eb7a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f75a2b48c90>]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w10['jet_lat'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5121606c-edbc-42ab-a441-fac3355ad9f9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f75a2b6fb10>]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w10['jet_speed'].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4131aac9-254d-485e-bd8e-ebad2f8d42a3",
   "metadata": {},
   "source": [
    "### Barnes & Polvani 2013"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0bfae945-7e33-4ccc-add2-4b28513233a7",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 353 ms, sys: 26.8 ms, total: 380 ms\n",
      "Wall time: 358 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# This takes ~500 milliseconds on Intel i7-10750\n",
    "## Look at only north atlantic and reduce filter freq and window size for Barnes & Polvani\n",
    "bp13 = jsmetrics.jet_statistics.barnes_polvani_2013(\\\n",
    "                    ua.sel(lon=slice(300, 360), lat=slice(70, 20),\\\n",
    "                           plev=slice(700, 850)),\\\n",
    "                    filter_freq=4, window_size=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ad5a5c87-3c48-4ce7-aec3-6fbe48335145",
   "metadata": {},
   "outputs": [
    {
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       "  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.Dataset&gt;\n",
       "Dimensions:    (lon: 60, lat: 51, plev: 2, time: 59)\n",
       "Coordinates:\n",
       "  * lon        (lon) float32 300.0 301.0 302.0 303.0 ... 356.0 357.0 358.0 359.0\n",
       "  * lat        (lat) float32 20.0 21.0 22.0 23.0 24.0 ... 67.0 68.0 69.0 70.0\n",
       "  * plev       (plev) int32 700 850\n",
       "  * time       (time) datetime64[ns] 2021-01-01 2021-01-02 ... 2021-02-28\n",
       "Data variables:\n",
       "    ua         (time, plev, lat, lon) float32 ...\n",
       "    jet_lat    (time) float64 nan nan nan nan nan nan ... nan nan nan nan nan\n",
       "    jet_speed  (time) float64 nan nan nan nan nan nan ... nan nan nan nan nan\n",
       "    jet_width  (time) float64 nan nan nan nan nan nan ... nan nan nan nan nan\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmw...</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-546564a4-8f40-418b-9a88-e5a71a6365c3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-546564a4-8f40-418b-9a88-e5a71a6365c3' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 60</li><li><span class='xr-has-index'>lat</span>: 51</li><li><span class='xr-has-index'>plev</span>: 2</li><li><span class='xr-has-index'>time</span>: 59</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f3e8af04-8cf7-4606-87c3-34361cf0a6fe' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f3e8af04-8cf7-4606-87c3-34361cf0a6fe' 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'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>300.0 301.0 302.0 ... 358.0 359.0</div><input id='attrs-9b070b72-4319-4cdb-aea5-5b750cdb2528' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b070b72-4319-4cdb-aea5-5b750cdb2528' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c371d22-b536-49a8-abc6-19a300f5327e' class='xr-var-data-in' type='checkbox'><label for='data-7c371d22-b536-49a8-abc6-19a300f5327e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([300., 301., 302., 303., 304., 305., 306., 307., 308., 309., 310., 311.,\n",
       "       312., 313., 314., 315., 316., 317., 318., 319., 320., 321., 322., 323.,\n",
       "       324., 325., 326., 327., 328., 329., 330., 331., 332., 333., 334., 335.,\n",
       "       336., 337., 338., 339., 340., 341., 342., 343., 344., 345., 346., 347.,\n",
       "       348., 349., 350., 351., 352., 353., 354., 355., 356., 357., 358., 359.],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 21.0 22.0 ... 68.0 69.0 70.0</div><input id='attrs-fc21d900-97fd-409d-bfb7-e8c824c1fc43' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fc21d900-97fd-409d-bfb7-e8c824c1fc43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7722d0f-ae42-4d8a-a357-a96bcac8108f' class='xr-var-data-in' type='checkbox'><label for='data-d7722d0f-ae42-4d8a-a357-a96bcac8108f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([20., 21., 22., 23., 24., 25., 26., 27., 28., 29., 30., 31., 32., 33.,\n",
       "       34., 35., 36., 37., 38., 39., 40., 41., 42., 43., 44., 45., 46., 47.,\n",
       "       48., 49., 50., 51., 52., 53., 54., 55., 56., 57., 58., 59., 60., 61.,\n",
       "       62., 63., 64., 65., 66., 67., 68., 69., 70.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>plev</span></div><div class='xr-var-dims'>(plev)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>700 850</div><input id='attrs-d80698f9-f73b-43f3-b91d-4194e532cd3b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d80698f9-f73b-43f3-b91d-4194e532cd3b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f519282-5559-4ac5-9d87-27356e74a984' class='xr-var-data-in' type='checkbox'><label for='data-9f519282-5559-4ac5-9d87-27356e74a984' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>millibars</dd><dt><span>long_name :</span></dt><dd>pressure_level</dd></dl></div><div class='xr-var-data'><pre>array([700, 850], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-01-01 ... 2021-02-28</div><input id='attrs-741c2f6b-6ff7-4cc2-b167-8f326d2bdf80' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-741c2f6b-6ff7-4cc2-b167-8f326d2bdf80' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52177102-2e56-47fd-9361-6a92fc7d11af' class='xr-var-data-in' type='checkbox'><label for='data-52177102-2e56-47fd-9361-6a92fc7d11af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T00:00:00.000000000&#x27;, &#x27;2021-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-03T00:00:00.000000000&#x27;, &#x27;2021-01-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-05T00:00:00.000000000&#x27;, &#x27;2021-01-06T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-07T00:00:00.000000000&#x27;, &#x27;2021-01-08T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-09T00:00:00.000000000&#x27;, &#x27;2021-01-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-11T00:00:00.000000000&#x27;, &#x27;2021-01-12T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-13T00:00:00.000000000&#x27;, &#x27;2021-01-14T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-15T00:00:00.000000000&#x27;, &#x27;2021-01-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-17T00:00:00.000000000&#x27;, &#x27;2021-01-18T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-19T00:00:00.000000000&#x27;, &#x27;2021-01-20T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-21T00:00:00.000000000&#x27;, &#x27;2021-01-22T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-23T00:00:00.000000000&#x27;, &#x27;2021-01-24T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-25T00:00:00.000000000&#x27;, &#x27;2021-01-26T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-27T00:00:00.000000000&#x27;, &#x27;2021-01-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-29T00:00:00.000000000&#x27;, &#x27;2021-01-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-31T00:00:00.000000000&#x27;, &#x27;2021-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-02T00:00:00.000000000&#x27;, &#x27;2021-02-03T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-04T00:00:00.000000000&#x27;, &#x27;2021-02-05T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-06T00:00:00.000000000&#x27;, &#x27;2021-02-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-08T00:00:00.000000000&#x27;, &#x27;2021-02-09T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-10T00:00:00.000000000&#x27;, &#x27;2021-02-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-12T00:00:00.000000000&#x27;, &#x27;2021-02-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-14T00:00:00.000000000&#x27;, &#x27;2021-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-16T00:00:00.000000000&#x27;, &#x27;2021-02-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-18T00:00:00.000000000&#x27;, &#x27;2021-02-19T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-20T00:00:00.000000000&#x27;, &#x27;2021-02-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-22T00:00:00.000000000&#x27;, &#x27;2021-02-23T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-24T00:00:00.000000000&#x27;, &#x27;2021-02-25T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-26T00:00:00.000000000&#x27;, &#x27;2021-02-27T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-28T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d4bc326c-588f-4323-bc93-7a1296c122d9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d4bc326c-588f-4323-bc93-7a1296c122d9' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ua</span></div><div class='xr-var-dims'>(time, plev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3f302e3a-d586-4a47-bd84-662b15e20ef1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f302e3a-d586-4a47-bd84-662b15e20ef1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-abcad4e3-e098-4928-a874-8baaaab4a0af' class='xr-var-data-in' type='checkbox'><label for='data-abcad4e3-e098-4928-a874-8baaaab4a0af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>U component of wind</dd><dt><span>standard_name :</span></dt><dd>eastward_wind</dd></dl></div><div class='xr-var-data'><pre>[361080 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jet_lat</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4d757ce7-2b77-4caf-89aa-5538153fcdf6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4d757ce7-2b77-4caf-89aa-5538153fcdf6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6340680f-136a-4e17-8b96-8691e4c4b084' class='xr-var-data-in' type='checkbox'><label for='data-6340680f-136a-4e17-8b96-8691e4c4b084' 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([  nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan, 53.39, 53.02, 46.86, 51.41, 54.41, 57.94, 58.83, 40.66,\n",
       "       37.89, 40.95, 41.9 , 41.76, 41.06, 39.3 , 38.85, 37.93, 36.61,\n",
       "       40.31, 39.88, 39.18, 39.06, 39.17, 41.84, 41.17, 41.04, 49.73,\n",
       "       47.15, 44.34, 43.85, 41.06, 40.28, 40.28, 40.91, 41.74, 42.02,\n",
       "       43.04, 45.16, 44.77, 43.94,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jet_speed</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-bb44f1d1-0445-4e51-a81a-9ff578859857' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bb44f1d1-0445-4e51-a81a-9ff578859857' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98f5f931-b1b2-457a-b8f7-6afb60c25a98' class='xr-var-data-in' type='checkbox'><label for='data-98f5f931-b1b2-457a-b8f7-6afb60c25a98' 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([        nan,         nan,         nan,         nan,         nan,\n",
       "               nan,         nan,         nan,         nan,         nan,\n",
       "       10.44741666, 12.09403548, 12.5934101 , 10.96221908, 10.80767583,\n",
       "       13.00249288, 13.48639645, 12.12326202, 15.21746624, 17.41413492,\n",
       "       18.77190495, 19.07447162, 18.55385101, 18.54324205, 18.10426893,\n",
       "       15.96469725, 13.98141684, 13.49758671, 15.5217395 , 18.4342207 ,\n",
       "       19.74383901, 18.64533611, 16.66208365, 13.38309035,  9.75669731,\n",
       "       10.02676443, 12.84030262, 16.89106813, 20.20687784, 21.96375049,\n",
       "       22.96743476, 22.45927236, 21.28453954, 19.95092565, 17.36934455,\n",
       "       15.70637521, 18.11623382, 21.02976958, 21.116424  ,         nan,\n",
       "               nan,         nan,         nan,         nan,         nan,\n",
       "               nan,         nan,         nan,         nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jet_width</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ea6f4094-19b6-47a2-9f5e-5d7e7cb10932' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ea6f4094-19b6-47a2-9f5e-5d7e7cb10932' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-360c13ef-de8d-4920-b849-72e3316a4f1d' class='xr-var-data-in' type='checkbox'><label for='data-360c13ef-de8d-4920-b849-72e3316a4f1d' 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([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 26., 23., 21.,\n",
       "       22., 24.,  9.,  7., 14., 16., 16., 15., 14., 15., 14., 14., 15.,\n",
       "       23., 23., 21., 19., 17., 17., 20., 21., 20., 15., 12., 14., 13.,\n",
       "       13., 12., 13., 14., 15., 19., 21., 18., 15., 15., nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5e9c111e-db26-40df-b48f-bd0cead0fea2' class='xr-section-summary-in' type='checkbox'  ><label for='section-5e9c111e-db26-40df-b48f-bd0cead0fea2' class='xr-section-summary' >Indexes: <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-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-85cd925c-4ae4-46f8-87bf-87ddc3744dff' class='xr-index-data-in' type='checkbox'/><label for='index-85cd925c-4ae4-46f8-87bf-87ddc3744dff' 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([300.0, 301.0, 302.0, 303.0, 304.0, 305.0, 306.0, 307.0, 308.0,\n",
       "              309.0, 310.0, 311.0, 312.0, 313.0, 314.0, 315.0, 316.0, 317.0,\n",
       "              318.0, 319.0, 320.0, 321.0, 322.0, 323.0, 324.0, 325.0, 326.0,\n",
       "              327.0, 328.0, 329.0, 330.0, 331.0, 332.0, 333.0, 334.0, 335.0,\n",
       "              336.0, 337.0, 338.0, 339.0, 340.0, 341.0, 342.0, 343.0, 344.0,\n",
       "              345.0, 346.0, 347.0, 348.0, 349.0, 350.0, 351.0, 352.0, 353.0,\n",
       "              354.0, 355.0, 356.0, 357.0, 358.0, 359.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;))</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-6389c3ec-cfb2-4fc4-bcdc-57b6bba45432' class='xr-index-data-in' type='checkbox'/><label for='index-6389c3ec-cfb2-4fc4-bcdc-57b6bba45432' 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([20.0, 21.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0,\n",
       "              31.0, 32.0, 33.0, 34.0, 35.0, 36.0, 37.0, 38.0, 39.0, 40.0, 41.0,\n",
       "              42.0, 43.0, 44.0, 45.0, 46.0, 47.0, 48.0, 49.0, 50.0, 51.0, 52.0,\n",
       "              53.0, 54.0, 55.0, 56.0, 57.0, 58.0, 59.0, 60.0, 61.0, 62.0, 63.0,\n",
       "              64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>plev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ed574af5-ed49-42ae-b922-a926e11a0738' class='xr-index-data-in' type='checkbox'/><label for='index-ed574af5-ed49-42ae-b922-a926e11a0738' 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([700, 850], dtype=&#x27;int64&#x27;, name=&#x27;plev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-eb8ee8e4-4768-4a2c-ab5c-a2fca31b67da' class='xr-index-data-in' type='checkbox'/><label for='index-eb8ee8e4-4768-4a2c-ab5c-a2fca31b67da' 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;2021-01-01&#x27;, &#x27;2021-01-02&#x27;, &#x27;2021-01-03&#x27;, &#x27;2021-01-04&#x27;,\n",
       "               &#x27;2021-01-05&#x27;, &#x27;2021-01-06&#x27;, &#x27;2021-01-07&#x27;, &#x27;2021-01-08&#x27;,\n",
       "               &#x27;2021-01-09&#x27;, &#x27;2021-01-10&#x27;, &#x27;2021-01-11&#x27;, &#x27;2021-01-12&#x27;,\n",
       "               &#x27;2021-01-13&#x27;, &#x27;2021-01-14&#x27;, &#x27;2021-01-15&#x27;, &#x27;2021-01-16&#x27;,\n",
       "               &#x27;2021-01-17&#x27;, &#x27;2021-01-18&#x27;, &#x27;2021-01-19&#x27;, &#x27;2021-01-20&#x27;,\n",
       "               &#x27;2021-01-21&#x27;, &#x27;2021-01-22&#x27;, &#x27;2021-01-23&#x27;, &#x27;2021-01-24&#x27;,\n",
       "               &#x27;2021-01-25&#x27;, &#x27;2021-01-26&#x27;, &#x27;2021-01-27&#x27;, &#x27;2021-01-28&#x27;,\n",
       "               &#x27;2021-01-29&#x27;, &#x27;2021-01-30&#x27;, &#x27;2021-01-31&#x27;, &#x27;2021-02-01&#x27;,\n",
       "               &#x27;2021-02-02&#x27;, &#x27;2021-02-03&#x27;, &#x27;2021-02-04&#x27;, &#x27;2021-02-05&#x27;,\n",
       "               &#x27;2021-02-06&#x27;, &#x27;2021-02-07&#x27;, &#x27;2021-02-08&#x27;, &#x27;2021-02-09&#x27;,\n",
       "               &#x27;2021-02-10&#x27;, &#x27;2021-02-11&#x27;, &#x27;2021-02-12&#x27;, &#x27;2021-02-13&#x27;,\n",
       "               &#x27;2021-02-14&#x27;, &#x27;2021-02-15&#x27;, &#x27;2021-02-16&#x27;, &#x27;2021-02-17&#x27;,\n",
       "               &#x27;2021-02-18&#x27;, &#x27;2021-02-19&#x27;, &#x27;2021-02-20&#x27;, &#x27;2021-02-21&#x27;,\n",
       "               &#x27;2021-02-22&#x27;, &#x27;2021-02-23&#x27;, &#x27;2021-02-24&#x27;, &#x27;2021-02-25&#x27;,\n",
       "               &#x27;2021-02-26&#x27;, &#x27;2021-02-27&#x27;, &#x27;2021-02-28&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-db82ef5c-a343-46b1-a23d-e44ed0d3dce4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-db82ef5c-a343-46b1-a23d-e44ed0d3dce4' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmwf/mars-client/bin/grib_to_netcdf -S param -o /cache/data6/adaptor.mars.internal-1645789868.3978655-14915-10-d5b8d9d1-2766-4630-b88f-1f6a21a2a0a4.nc /cache/tmp/d5b8d9d1-2766-4630-b88f-1f6a21a2a0a4-adaptor.mars.internal-1645789330.2418482-14915-17-tmp.grib</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (lon: 60, lat: 51, plev: 2, time: 59)\n",
       "Coordinates:\n",
       "  * lon        (lon) float32 300.0 301.0 302.0 303.0 ... 356.0 357.0 358.0 359.0\n",
       "  * lat        (lat) float32 20.0 21.0 22.0 23.0 24.0 ... 67.0 68.0 69.0 70.0\n",
       "  * plev       (plev) int32 700 850\n",
       "  * time       (time) datetime64[ns] 2021-01-01 2021-01-02 ... 2021-02-28\n",
       "Data variables:\n",
       "    ua         (time, plev, lat, lon) float32 ...\n",
       "    jet_lat    (time) float64 nan nan nan nan nan nan ... nan nan nan nan nan\n",
       "    jet_speed  (time) float64 nan nan nan nan nan nan ... nan nan nan nan nan\n",
       "    jet_width  (time) float64 nan nan nan nan nan nan ... nan nan nan nan nan\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmw..."
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bp13"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "34634186-d7b9-4a09-bee8-6579ed9740a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f759aa85610>]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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BYMBXX30FH5/W/0A35+TJkygsLERsbPPpHaPRiKCgoCY3tbGkwSyzM0qnA+TVZfIsU2v8mAIjOzTsAdS+GaCIACNGdbekwTgLRERKcmkANH/+fHz88cf4z3/+g8DAQOTm5iI3NxeVlZUAGoKf8vJyvP/++zCZTLZjGtfz9OnTB6tXrwYAlJWV4aGHHsK2bdtw4sQJbNy4ETNnzkSPHj2QkpLiktepFLk+Z8MB5dJg2UUV2JNdDI0EpFwg/QXAVsjKFBi1hW0X6HamwABgxkBLU15H1b8RkXdyaQD01ltvoaSkBBMnTkRsbKzt9tlnnwEAUlNTsX37duzbtw89evRockzjNFVaWpptBZlWq8XevXtxxRVXoFevXrj99tsxdOhQ/PLLLzAa2zcNrxYjuoYhIsCA4opabFEoDSbPJo3sGo6owAvPrvlaU2DcCJHaQi6CDmtnCgwAUvpHQ6uRsP+UCZmF5UoNjYi8nEv3ARKi9Q7nEydOvOAx557H19cX3377bYfHpkZyGuzjbVlYtzcHE3pFdvicclphRhvSX0BDK4xKtsKgNpCXwXdkBig8wIjR3cPxy9ECrNt3uk0NVYmILkQVRdDUdnI64NsDeaip61gaLKuwAntPlkAjwVZfdCFyM1TOAFFbdLQGSCanf53VFJiIPB8DIDdjSYMZUVJZi9+OFXToXPLsz0XdwhER0LYUhb+RGyFS2zXUAHUs/ZzSPwZajYQDOSZkFDANRkQdxwDIzWg1EqYPtMzWdOTTcHFFDZb/lgGg7ekvgBshUtsJIWw1QB2dAQr1N2B0d26KSETKYQDkhuR0wLcHctudBnvm64PIL61Gt0h/XDXk/L2XWsJWGNRWFTX1qLb+fHakBkgmb9OwlmkwIlIAAyA3NKxLGKICjSitqsOv6Wfsfvx3B3KxetcpaCTg5WuS4aNve48m7gNEbSUXQPvoNbYNNDtiSr8Y6DQSDp024diZsg6fj4i8GwMgN6TVSLaWFev25tr12LPlNXhs9X4AwLzx3TEkIdSux8spMO4ETRdSaG2D0d5doM8V6m/AmB4RAID1nAUiog5iAOSmZiRZVoN9dzAX1XVtD0ae+uoACsqq0TMqAPdP7mn38zZOgbVliwLyXkosgT8Xe4MRkVIYALmpYYmhDWmwo21bDbZh/2l8tScHWo1kd+pLJs8A1ZkFahRuykqeRakl8I2l9IuBXivhcG4p0vOZBiOi9mMA5KY0GgnT7dgbpbCsGo9bU193TeiG5PiQdj2vXAMEsBCaWlcgd4JXKAUGAMF+eoyV02CcBSKiDmAA5MbkVTHfH8xDVW3rwcjirw6gsLwGvaMDce8k+1NfMr1WA4PW8mNTzgCIWlHkgBQY0JD+5aaIRNQRDIDc2JCEUMQE+aC0ug6/tJIGW7f3NNbtPW1LfRl19qe+GvOT22FwJRi1Qqk9gM51ab9o6LUS0vJKcTSvVNFzE5H3YADkxpqmwZrvlF1QVo0nv7SkvuZP7I6BnYM7/Lx+bIdBbdDQCFXZACjYV49xPS198FgMTUTtxQDIzc1IsiyHby4NJoTAk2v2o6i8Bn1iArHgkvanvhrzs7bD4FJ4ao3cBqOtbVbswd5gRNRRDIDc3OD4UMQG+6C8ph6bjzTdFPHrvafxzf5c6DQSXrk2GQadMm+3n20vIKbAqGVFDpoBAoDJ/aJh0GpwNL8MR5gGI6J2YADk5hqnwRqviskvrcJia+prwSU90D+u46kvmR83Q6QLEEI4ZB8gWbCvHuN7WVaDsTUGEbUHAyAPIG8O94M1DSaEwOOr96O4ohb9YoMw/+Ieij6f3NaAM0DUkrLqOts+UUrtBH0u26aIe3O4KScR2a3jDXrI5QbHh6BTiC9OFVdiU9oZVNXW4/uDedBrLakvvVbZOJftMOhC5NkfP4PW9vOitMl9o2HQaXDsTDmO5JWhd0ygQ56HiDwTZ4A8gCRJmD7QUgz90bYTeOqrAwCAey/pib6xQYo/nz8DILoAR60AayzQR48JvayrwVpYBUlE1BIGQB5C3hzut/RClFTWYmCnYNw1sbtDnospMLoQeQVYuANWgDUmbwa6dt9ppsGIyC4MgDxEcudgdArxBQAYtBq8fI3yqS8Zi6DpQhzRB6w5k6xpsONnynHotOevBjuYY8Jlf/8FX+w86eqhkBux1IXuw0Mr98Bs5gcFGQMgDyFJEm4cmQAAeCilt0PrIWwBEDdCpBY4ahfocwUYdZhoTYN5em+wqtp63PfpLuw/ZcJjq/fh2Bk2g6W2OZBjwifbs7By50kcZRNhGwZAHuTuCd2xbdEk3Dm+m0Ofx5YCu0D/MfJechF0mAOWwJ/LthrMw9Ngb2w8avvjVV1nxsKVe1DPT/PUBo0/HKRmnXXhSNSFAZAH0WgkxAT7OPx5GmaAWANEzSuydoKPcNAS+MYm9Y2GUadBRkE5Dp42Ofz5XGFX1lm8s/kYAODpy/sh0KjDrqxivPfLcRePjNROCNGkZUxqJgMgGQMgshtbYdCFOGMVmCzAqMPFvaMAeGZrjKraeixcuQdmAcwcFIdbxnTFk5f1AwC88v0RNoSlVh3IMSGzsML2NWeAGjAAIrvJzVC5Coxa4shdoJvjyWmw174/gmNnyhEZaMTTl/cHAFwzrDMm9o5EjTUVVmfddJLoXPJO6aO6hQMAjp0pR3FFjSuHpBoMgMhufkauAqPWFVpTYI7aBfpcl/SJgo9eg8zCChzI8Zw02M7MIrxrTXO9MHsgQq0zapIk4cUrkxDoo8OekyW2Y4gas6S/LHtk/WlUIrpG+AMAdmUVu3BU6sEAiOzWsA8QAyA6nxCioRGqk2aA/I06XNLHmgbzkNVglTX1WLhyL4QArhzSCZf2i27y/ZhgH9uM0OvfH0VaLlNh1NS+UyXILqqEr16Li3tHYXBCCACmwWQMgMhu7AZPrTFV1aG23pKGcvQy+MbkpsDr9npGGuzl79KQUVCO6CAjnrqsf7PHXDmkEyb3jUJNvSUVVstUGDUi18Rd0jcKvgYthiaGAmAAJGMARHbjRojUGnn2x9+ghY/eMX3AmiOnwbKKKrD/lHunwX4/UYQPfssAACy9ciCC/fTNHidJEl6YPRDBvnrsO1WCtzcdc+YwScWEELb6n8usHw6GJFgCoN1ZxdxCAQyAqB3kFFh1nZn/iOg8zmqDcS4/gw6T+ljSRGv3uW9vsIqaOjy0cg+EAK4Z2hmX9Ilu9fioIB88c4VlhujNH4/ikIduBUD22XOyBKeKK+Fn0GKidZVkr+hABBh1KK+pZ8oUDICoHfwadfdmGozO5cwl8OeyrQZz4zTYSxvScKKwArHBPnjCutz9QmYOisOUftGorRd48H9MhVHD5oeT+kbD1/o7W6uRMCg+BADTYAADIGoHo04DjWT5f6bB6FzyEvgIJxVAN3Zx7yj46rU4ebYSe0+WOP35O2rb8UKs2HICAPDiVUkI9m0+9XUuSZLw/OyBCPXT4+BpE5b9lO7AUZLaCSFs9T8zrOkv2RAWQtswACK7SZIEf64EoxbIu0C7YgbI16DFpL7uuRqsvLoOD3++FwBw/fB4TLD2OGuryEAjnp05AADwjx/Tsf+U+wWApIzd2cU4VVwJf4MWE3s3/TkabC2E5lJ4FwdAS5cuxfDhwxEYGIioqCjMmjULaWlpTY6pqqrC/PnzER4ejoCAAFx11VXIy8tr9bxCCCxevBixsbHw9fXF5MmTcfToUUe+FK8jT6mWsx0GnaPAtgmic2uAZJe5aRrsrxsOI6uoAnHBPnh8Rt92neOypFhMHxiDOrPAwpV7UFPHVJg3kmd/JveLPm8hwpB4SwCUUVBuq9fzVi4NgDZv3oz58+dj27Zt+P7771FbW4spU6agvLzcdsxf/vIXfP3111i5ciU2b96MnJwcXHnlla2e96WXXsKbb76Jt99+G9u3b4e/vz9SUlJQVVXl6JfkNfyt7TAq2RCVzlHkpE7wLZnYOwp+Bi1OFVdij5ukwbYcK8CHWzMBAC9dnYxAn7alvs4lSRKenTkAYf4GHM4txT9+5Ac/b2M2C1v9z7npLwAI9tOjR1QAAM4CuTQA2rBhA2655Rb0798fycnJWLFiBbKysrBz504AQElJCd5//328+uqruOSSSzB06FAsX74cW7ZswbZt25o9pxACr7/+Op544gnMnDkTSUlJ+PDDD5GTk4M1a9Y48dV5Nl89Z4CoebZdoF1QAwQAPnotJvW1rJxat1f9q8HKGqW+bhqZgLE9Izp0vogAI56zpsKWbTqGfW4SBJIydmUXI6ekCgFGHca3kEZlHZCFqmqASkos/1DDwsIAADt37kRtbS0mT55sO6ZPnz5ISEjA1q1bmz1HRkYGcnNzmzwmODgYI0eObPExZD9/azuMStYA0TnkIugwJ7XBaM4MN9oUcen6Qzh5thKdQnyxaHr7Ul/nmpEUi8uSYlFvFnhw5W5U1/HfqbeQ01+XNpP+ksn7ATEAUgmz2Yz7778fY8aMwYABlk8vubm5MBgMCAkJaXJsdHQ0cnNzmz2PfH90dNO9M1p7THV1NUwmU5Mbtc6XRdDUgkIXp8AAYGLvSPgbtMgpqcKu7GKXjeNCDuaY8Mn2LADA365OQoA1tayEZ2cOQESAAUfyyvDJtizFzkvq1Tj9Nb2Z9JdsiLUQek92iVc30lVNADR//nzs378fn376qdOfe+nSpQgODrbd4uPjnT4Gd8OO8NQcIQTOlju3E3xzfPRaTO4np8HUuxrs1/QzACy7WI/u0bHU17nC/A24dUxXAJaeUOT5UrPOItdUhUCjDuNaSaX2iAxAoI8OlbX1OOzFGyKqIgBasGAB1q5di59++gmdO3e23R8TE4OamhoUFxc3OT4vLw8xMTHNnku+/9yVYq09ZtGiRSgpKbHdsrOzO/BqvAM7wlNzTJV1qLPuDu6KZfCNyWmw9ftOw6zSHctTM4sBAMO7hDnk/F3CLd2/s4oqHHJ+Uhd564fW0l8AoNFIGMw0mGsDICEEFixYgNWrV+PHH39E165dm3x/6NCh0Ov12Lhxo+2+tLQ0ZGVlYdSoUc2es2vXroiJiWnyGJPJhO3bt7f4GKPRiKCgoCY3ap28G3Q5AyBqpMBaAB1o1MGoc14fsOaM7xWJAKMOp0uqsCtbfb/khRC2Pz5yk0qlJYb7AQAyCxkAebomq7+SWk5/yWyF0Jnq+7fhLC4NgObPn4+PP/4Y//nPfxAYGIjc3Fzk5uaisrISgKV4+fbbb8cDDzyAn376CTt37sStt96KUaNG4aKLLrKdp0+fPli9ejUAyzLQ+++/H0uWLMFXX32Fffv2Yc6cOYiLi8OsWbNc8TI9krwRYiVTYNRIkQrSXzIfvRaXWtNga1WYBjtVXIn80mroNBKSOgc75DniwywBUEFZNdPVHm5n1lnkmaoR6KNr00pCuRB6J2eAXOOtt95CSUkJJk6ciNjYWNvts88+sx3z2muv4bLLLsNVV12F8ePHIyYmBqtWrWpynrS0NNsKMgB4+OGHcc8992DevHkYPnw4ysrKsGHDBvj4+DjttXk6X84AUTPkjdVcnf6STVdxGmyn9ZN3v7igVtMVHRHsq7e108guqnTIc5A6yLVuU/rFtGn2dVBCCCTJ8nNxptQ7N0RUbslBO7RleaqPjw+WLVuGZcuWtfk8kiTh2WefxbPPPtvhMVLzGmaAGABRg4ZGqK5bAt/YuJ4RCDTqkGeqRmrWWQxzUK1Ne8ib0MmfxB0lMdwPe0+WILOwHL1jAh36XOQa9Y3SX5e1If0FAEE+evSKCkRaXilSs84ipX/zNbKeTBVF0OR+2AqDmuPKRqjNUXMaTK7/GeKg+h+ZnAZjIbTn+uNEEfJLqxHko8MYO1YTDkkMAeC9hdAMgKhdbBshshUGNVJkmwFSRwAENBSEqikNVllTj4M5lv3G5GJUR0lgAOTx5NVfKf1jYNC1/c+6bSWYlxZCMwCidvHVW1JgnAGixgrK5DYY6kiBAcDYnhEI9NEhv7Qaf6jkF/3ek8WoMwtEBRrRKcTXoc+VyADIo1nSX5ZNftuy+qsxefXh3pMlXtk4lwEQtYu8DJ77AFFjrm6E2hyjTosp/Sz1DWrpDZbaqP5HkiSHPhdngDzbjowiFJRVI9hXb1f6CwC6RfgjxE+P6jozDp32vg4IDICoXZgCo+bINUBqWAbfmFwYun5/LupVkAZz9P4/jSVY9wI6WVSpitdOylpvS39FQ6+170+6JEkYHB8CwDvrgBgAUbs0pMAYAFGDQhXWAAHAmB4RCPLR4UxpNX4/UeTSsQghsMtWAB3i8OeLDfaFTiOhpt6MPFOVw5+PnKfeLPDNfnnzw7h2ncO2H5BK0sPOxACI2qWhGzxrgMjCbBY4WyGvAlNPDRAAGHQaTOkvp8Fcuxosq6gCBWU10Gsl9I9zzAaIjWk1EjqH+tqemzzH9oxCFJTVIMRPj9Hdw9t1DnkWUt6WwZswAKJ2kZfBV9TWt2k/J/J8JZW1thRLqJ+6ZoCAhgLRb1ycBpNTDf3jgh22AeK5EuSeYGyJ4VHkYH5q/xi701+y5PgQaCTLzuTeNkPIAIjaRd4IUQigqtb7Vg/Q+QqtfcCCfHR2LcV1ljHdIxDsq0dBWTV2ZLguDSY3QHVG/Y8sIYwzQJ6mrt6MDfvbt/qrMX+jDr1jLP0vvW05vPp+S5Fb8G30ybWcaTBC4wJodaW/ZAadBin9LZsirtvnutVgtg0QHbwDdGNcCeZ5tmcUobC8BqF+eozq1r70l2yotRbN2+qAGABRu2g0ki0IYjsMAhoKoNW0BP5ccqHohv25qKt3/sxleXWdbbmxMwqgZQlhlhRYJgMgjyHvbD51QCx07Ux/yeRg3NtWgjEAonbzszVE5QwQqXcFWGOju4cjxE+PgrIabHdBGmzPyWKYBRAb7IPYYMdugNiYPAOUzQDIY2xKywcATB/Y8R5ecgC0/5QJ1XXe84GWARC1m5+RmyFSgyKVp8AAQK/VIEXeFHGf81eD2RqgOrH+B2jYC6iovAalVbVOfW5SXkllLU6XWAqWB1n38emIxHA/hPkbUFNvxoEc79kQkQEQtZufnh3hqYFcBK3mFBjQUDDqijSYXGPhzPofAAgw6mzvC+uA3N/RvFIAQFywDwJ99B0+nyRJDWkwL6oDYgBE7caO8NSYrQZIZbtAn2tU93CE+ulRVF6DbcedlwZrsgGigxugNieeaTCPcSSvDADQMzpQsXN6Y2d4BkDUbmyHQY0VWhuhqrkGCLCkwaYOkNNgzlsNllFQjrMVtTDoNE7ZAPFcXAnmOY5YZ4B6RQcods6GGaBixc6pdgyAqN3YDoMaa2iEqt4aINmMgQ2rwWqdlAaTG6AmdQp2yT5JidY6oExuhuj2juZbAiAlZ4CSOgdDq5GQa6pCTnGlYudVMwZA1G7+tiJopsBIvY1Qm3NRtzCE+RtwtqIW244XOuU5bfU/Ti6AlsVzBshjyCmwXgoGQH4GHfrFWjZE9Jb9gBgAUbvJy+C5CozqG/UBU3sRNADoGqfBnNQbzJX1PwBTYJ6iuKIGZ0ot6eaeUcqlwICGn01vqQNiAETt5mdth8EAiIoraiC31wp1gwAIAC4baF0NdsDxabDSqlqkWes2nL0CTCanwE6drXTJJpCkDHn2p1OIL/yNOkXPLc9OpnpJY1QGQNRuDTNATIF5O7n+J9hX3+6mjM42omsYIgIMKK6oxZZjjk2D7ckugRBA51BfRAX5OPS5WhId6AODToM6s7DtIUPuxxEF0DI5OD+YU4IqL1jc4h6/qUiVOANEsgI3qv+RNU2DOXY1mKv2/2lMo5EQH8qmqO7uqC0AUq7+R9Y51BeRgUbU1gvsO1Wi+PnVhgEQtRtngEhW5AZ9wJojrwb79kAeauoclxZKdXH9j4x1QO5PToH1ULj+B5A3RAwB4B0bIjIAonZjETTJGnaBVv8S+MYsaTAjSipr8duxAoc8h9ncsAHi0MQwhzxHWzEAcn/yEnhHzAAB3tUYlQEQtRtTYCSTl8CHuVEKDAC0GgnTHLwa7HhBGUxVdfDRa9An1jF/tNoqIdzSFT6LewG5paLyGlu62REzQEDTQmghhEOeQy3aVUJuNpuRnp6O/Px8mM1Np43Hjx+vyMBI/ZgCI5k8AxThZikwwNIb7KNtmfjuQC5qZg9UfJNCuf4nqXOIywvEOQPk3uQC6M6hyq8Akw3sFAy9VsKZ0mqcPFtp2z/KE9l9Bbdt24Ybb7wRmZmZ50WHkiShvp6zAd6CKTCSyTVAam+D0ZzhXcIQGWjEmdJq/JZegIv7RCl6frm1gCsLoGUMgNybIwugZT56LfrFBWNPdjFSs856dABk98eRu+66C8OGDcP+/ftRVFSEs2fP2m5FRc5rLEiuZ0uBsRWG12tYBeZeNUCAJQ023ZoGW+uANFiqrf5HPQFQSWUtSipqXTwasldDE1THpL9k3lIIbXcAdPToUbzwwgvo27cvQkJCEBwc3ORG3sOPrTDIyl1XgclmJFlWg313MBfVdcoF9CWVtTiab/mjNdjFK8AAwNegRWSgJUjlLJD7se0BFOXYWjJ5tnKnhxdC2x0AjRw5Eunp6Y4YC7kZpsBIZguA3HAGCACGJYYiKtCI0qo6/HpUudVg8uqvxHA/RKjk2jAN5r7kYNqRKTCgYbby0OlSj/6A26YaoL1799r+/5577sGDDz6I3NxcDBw4EHq9vsmxSUlJyo6QVEtOgdWZBWrqzC7pcE2u17gPmDvWAAGWTQKnD4zFii0nsG7vaUzqG63IeeWWAmqo/5ElhvlhZ+ZZZBaVu3ooZIfCsmoUlddAkhy3AkwWF+KLmCAf5JqqsPdkCS7qFu7Q53OVNgVAgwYNgiRJTYqeb7vtNtv/y99jEbR3kWeAAEsazKBzzz9+1DFnK2ogBCBJQKif/sIPUKnLkiwB0PcH81BVWw8fvfbCD7oAWwNUFdT/yOSi1mzOALkVuf4nPtQPvoaO/2xeyJDEEKzfl4vUrLPeHQBlZGQ4ehzkhvRaDQxaDWrqzaioqUeI5y4WoFbIewCF+Oqhc5M+YM0ZkhBq+9T7y9ECXNqvY7NA9WaB3bYZoJCOD1AhTIG5p4YNEB07+yMbkhBqCYCsqxg9UZt+WyUmJtpumZmZ6NSpU5P7EhMT0alTJ2RmZjp6vKQyvqwD8nryHkDumv6SyWkwQJneYEfzS1FaXQc/gxa9HVyzYQ+5K3wmN0N0K3IBdE8n/Sw1bIh41mM3RLT749rFF1/c7HL3kpISXHzxxXad6+eff8bll1+OuLg4SJKENWvWNPm+JEnN3v72t7+1eM6nn376vOP79Olj17io7fy5GaLXK3TjJfDnmpFkWQ7/w6H8DnfDlj85J3cOUdXMmDwDlFNcidp6x/U/I2XJKTBnzQD1jwuCQatBUXmNxwbLdv+rlGt9zlVYWAh/f3+7zlVeXo7k5GQsW7as2e+fPn26ye2DDz6AJEm46qqrWj1v//79mzzu119/tWtc1HacASJ3XwLf2OD4UMQG+6Csug4/HznToXOpaf+fxiIDjfDRa2AWwKmzla4eDrWBEMK2CWJPBy+Blxl1WgzoFATAc/uCtXkn6CuvvBKAZVbmlltugdHY8Gmvvr4ee/fuxejRo+168mnTpmHatGktfj8mJqbJ119++SUuvvhidOvWrdXz6nS68x5LjtHQD4wzQN6qsMzaCNXN+oA1R06Dvf9rBtbtO40p/dv/e8TWAT4xRKHRKUOSJCSE+eFIXhmyiirQJcK+D67kfAVlNThbUQuNE1aANTY0MRSpWZYdoa8c0tlpz+ssbZ4Bkjc6FEIgMDCwyeaHMTExmDdvHj7++GOHDTQvLw/r1q3D7bfffsFjjx49iri4OHTr1g033XQTsrKyWj2+uroaJpOpyY3ahnsBUaGtDYb7p8AAS28wAPjBuhqsPc6W1+D4Gcsy88Hx6poBAlgI7W7k2Z+EMD9FVie2lW1DRA8thG7zDNDy5csBAF26dMHChQvtTnd11L///W8EBgbaZqJaMnLkSKxYsQK9e/fG6dOn8cwzz2DcuHHYv38/AgObnzpcunQpnnnmGUcM2+PZAiC2w/Bacg1QhAfMAAHA4PgQdArxxaniSmxKO4OpA+yfBdqVbZn96Rbhj1AVpgYTwqxd4RkAuQVnF0DL5ELotFwTyqrrEOCgBqyuYncN0FNPPeX04AcAPvjgA9x0003w8fFp9bhp06bhmmuuQVJSElJSUrB+/XoUFxfjf//7X4uPWbRoEUpKSmy37OxspYfvsfyMTIF5O3duhNocSZIwfaAl6Fm3r329wWwNUFVW/yNLCPMFAGR5aHGrpzli3QG6pxPTXwAQHeSDTiG+MAtgb3axU5/bGdoUzg0ePLjZwufmpKamdmhAzfnll1+QlpaGzz77zO7HhoSEoFevXq227zAajU1qmqjt/KzTseVMgXmtAusy+HAPSYEBlt5g//olAxsP5aGypt7ujeds9T8q2gG6sYRwpsDciTO6wLdkSGIoThVXIjXrLEb3iHD68ztSm2aAZs2ahZkzZ2LmzJlISUnBsWPHYDQaMXHiREycOBE+Pj44duwYUlJSHDLI999/H0OHDkVycrLdjy0rK8OxY8cQGxvrgJGRv3UGqJIBkNdq6APmGTNAAJDcORidQnxRUVOPTWn5dj22rt6M3dZPy2orgJY1ToF56h4vnkII4bQu8M2RN/Hc6YGd4ds0A/TUU0/Z/v+OO+7Avffei+eee+68Y+xNHZWVlTWZmcnIyMDu3bsRFhaGhIQEAIDJZMLKlSvxyiuvNHuOSZMmYfbs2ViwYAEAYOHChbj88suRmJiInJwcPPXUU9BqtbjhhhvsGhu1jfzJuJwpMK9UW29GcUUtAM9YBi+TJAmXJcXinZ+PY+2+05g2sO0foNLySlFRU49Ao85pS5bt1TnUkgIrq67D2Ypaj0lfeqIzpdUoqbSsAOse6YoAyDKLuSu7uMVtcNyV3TVAK1euxJw5c867/+abb8YXX3xh17n++OMPDB48GIMHDwYAPPDAAxg8eDAWL15sO+bTTz+FEKLFAObYsWMoKGjo3nzy5EnccMMN6N27N6699lqEh4dj27ZtiIyMtGts1DbyRoicAfJOchNUSQJC/Dzrj6i8GuzHQ/l2/XzLDVAHJYRAq1HnHwsfvRYxQZZ6SqbB1E2e/UkM93fqCjBZ39ggGHUaFFfU4niBZzXQtbuk29fXF7/99ht69uzZ5P7ffvvtggXK55o4ceIFp1/nzZuHefPmtfj9EydONPn6008/tWsM1DG+tn2AGAB5I3kFWJifQbV/7NtrYKdgxIf5IruoEj+l5dvaZFzILmuqYLBK639kCeF+yDVVIbOwHIPiQ1w9HGqBbQWYkwugZQadBsmdQ7DjRBFSM8+6ZBbKUewOgO6//37cfffdSE1NxYgRIwAA27dvxwcffIAnn3xS8QGSuvmxFYZX87QVYI1ZVoPF4p3Nx7Eq9ST6xLQtnfV7pqVVkJoaoDYnIcwPOzKK2BVe5RqaoLounTo40RoAZZ3FNcPiXTYOpdkdAD366KPo1q0b3njjDdvGh3379sXy5ctx7bXXKj5AUjduhOjdCjxoF+jmXDYwDu9sPo4fDuXjh0P2FUOrfgaImyG6BVcWQMvkOiBP6wzfrl2Nrr32WgY7BKChFQaXwXunhj5gnrMEvrEBnYIwfWAMfj1acOGDG5mRFIdgX72DRqUMdoVXP8sKMNfPAMkB0JH8UpiqahHko+6f7bbyrG0dyekaiqCZAvNGnrgEvjFJkvDPm4a6ehgOEW+dAWIKTL3yTNUoraqDViOhW6TrerZFBhqREOaHrKIK7MkuxrienrGoqE0BUFhYGI4cOYKIiAiEhoa2ugyuqKhIscGR+tmWwbMVhlcqKPPcGiBPJ6fATpuqUF1XD6PO+SuMqHXy7E9iuJ/L358hCSHIKqrAzsyz3hUAvfbaa7Y+Wq+99ppH7QNAHWPbCLGdTSPJvRXZdoFmAORuwv0N8DdoUV5Tj5NnKz1qdY+nsKW/VLCf1JDEUKzZnWPb5sETtCkAmjt3ru3/b7nlFkeNhdyQr9wKo5opMG8kL4MPD/DMGiBPJkkS4sP8cDi3FFlFFQyAVOiotQC6lwsLoGW2DRGzzsJsFtB4wLYXdm+EOGfOHCxfvhzHjh1zxHjIzcgzQNV1ZtSbuaW+t/HkZfDeQC6EZlNUdTqS75ou8M3pExMIP4MWpVV1SD9T5urhKMLuAMhgMGDp0qXo2bMn4uPjcfPNN+O9997D0aNHHTE+Ujm/Rk0iuReQ95GXwUd4aBG0p+NSePUSQiDdNgPk+gBIp9UgqXMwACDVQ/qC2R0Avffeezhy5Aiys7Px0ksvISAgAK+88gr69OmDzp07O2KMpGJGnQbyTCjbYXiXmjozTFWWoDfMQ5fBezoGQOqVa6pCabVlBVjXCNetAGvMth9QlpcGQLLQ0FCEh4cjNDQUISEh0Ol07LflhSRJsu0FxM0QvYvcB0wjASEq3/OGmpcQbu0KzxSY6sgbIHYJ94NB1+4/1YoamigHQMWuHYhC7L6qjz32GEaPHo3w8HA8+uijqKqqwqOPPorc3Fzs2rXLEWMklWNHeO9U2GgJvCcURHqjxjNAF+rLSM51VAUbIJ5L3t08Pb8MxdYPQO7M7o0QX3zxRURGRuKpp57ClVdeiV69ejliXORG/A1anAFTYN6m0LYEnukvd9UpxBcaybKNRUFZDSID+V6qha0JqooCoDB/A7pG+COjoBy7sotxce8oVw+pQ+yeAdq1axcef/xx7NixA2PGjEGnTp1w44034t1338WRI0ccMUZSOV+2w/BKXAHm/gw6DWKDfQEAWUXlLh4NNXZERUvgGxtsbfK7ywMKoe0OgJKTk3Hvvfdi1apVOHPmDNavXw+DwYD58+ejb9++jhgjqRzbYXingjLPboPhLVgIrT5CCKTnq2cFWGOeVAdkdwpMCIFdu3Zh06ZN2LRpE3799VeYTCYkJSVhwoQJjhgjqRzbYXgn7gLtGRLC/LD1eCGyCitdPRSyyimpQll1HXQaCV3C1bECTNZ4Q8R6s4DWjev/7A6AwsLCUFZWhuTkZEyYMAF33nknxo0bh5CQEAcMj9yBv7wKjO0wvAp3gfYMCXJXeKbAVEOu/+ka4a+aFWCyXtGBCDDqUFZdhyN5pegbG+TqIbWb3QHQxx9/jHHjxiEoqPUXffLkScTFxUGjUdebR8qTN0OsYDsMr1LIGiCPkMCu8KqjxhVgMq1GQnJ8MH5LL0Rq1lnvCoBmzJjRpuP69euH3bt3o1u3bnYPityLn9EaAKm4CLq23oyVf5xESWVtmx9j0Glw9ZDOCPbjHjfNKeQu0B6BNUDqIxdA91RZAbRsaEKoJQDKLMZNIxNdPZx2szsAaivuKeE95I0Q1dwR/r87srD4ywN2P+6Xo2ew/JbhkCT3zXM7SsMqMKbA3JncDyzPVI2q2nr46LUXeAQ5mppngABgcKJn7AjtsACIvIefQf0d4b/anQMAGNUtHJ1DfS94vADw1Z4cbEo7g5V/nMS1w+MdPEL3I6fAuArMvQX76hHoo0NpVR2yiypUte+MNzKbBY7mq3MJvGxIvCUAyigoR1F5jdumwRkAUYf52ZbBq3MG6HRJJf7IPAtJAl67bhBign3a9LieUQFY+s1hPLf2IMb2jEBcyIUDJ29RXVePUmsfMK4Cc2+SJCEx3A/7T5mQWcgAyNVOFVeioqYeeq2ERJWtAJMF++nRIyoA6fll2JV1FpP6Rrt6SO3CCmXqsIaNENU5A7R+Xy4AYHhiWJuDHwC4Y1w3DE4IQWl1HR75Yi/Tuo2cLbfUUmk1EoJ8WCPl7lgHpB5H8y3pr24RAdBr1fsneoh1Q0R3ToM57OqyZsJ7yBshqrUIet1eS/prRlKsXY/TaiS8fE0yjDoNfjlagE9/z3bE8NxSgbUAmn3APEM8AyDVUHsBtEzeD2inG+8I7bAAiJ+WvYefigOgU8WVSM0qhiQB0wbE2P347pEBeCilNwBgydqDOHmWfyCAhgJopr88Q2KYtSs8AyCXO6LyAmjZEGsh9J7sEtTVm108mvaxOwC67bbbUFpaet795eXluO2222xfHzx4EImJ7rs8jtpOXgWmxgDom32nAQAjuoQhKqjt6a/Gbh3TFcMSQ1FeU89UmJWtESoLoD0CU2DqcVSlPcDO1SMyAIE+OlTW1uNw7vkxgTuwOwD697//jcrK87dMr6ysxIcffmj7Oj4+Hlotl1N6g4YZIPXVAK3dawmALrMz/dWYViPhb9ckw0evwW/phfhke5ZSw3Nb8i7QXALvGRpvhmg2M8B3FbO5oQeY2ovRNRoJgxu1xXBHbQ6ATCYTSkpKIIRAaWkpTCaT7Xb27FmsX78eUVFRjhwrqZRaZ4BOnq3A7uxiaCQgpR3pr8a6Rvjj4ZQ+AIAX1h/y+l1zC5kC8yhxIT7QaiRU15mRX1rt6uF4rZNnK1FZWw+DVoNEa1CqZnIhtLvWAbV5GXxISAgkSYIkSejVq9d535ckCc8884yigyP3oNZWGN9YV3+N6BqGqMD2pb8au2V0F2zYn4sdJ4rw0Od78J87LvLaAuCiMgZAnkSn1aBTiC+yiiqQVVRh12pJUo5c/9Mt0h86Fa8Ak8mF0O7aGb7NAdBPP/0EIQQuueQSfPHFFwgLC7N9z2AwIDExEXFxcQ4ZJKmbrRVGbT2EEKpZAbjWWv8zI0mZn0uNRsLfrknC1Nd/wbbjRfhoWybmju6iyLndTUMNEFNgniIhzM8WAI3oGnbhB5DijliXwKs9/SUblBACSbLUjhWUVSPCzX4ftDkAmjBhAgAgIyMDCQkJqvkjR64np8CEAKrrzKrYSj+7qAJ7rOmvqf07lv5qLDHcH4um98HiLw/gxW8OY2LvSNVuVuZIbITqeRLC/YB0IKuQXeFdJV0ugI5SdwG0LMhHj15RgUjLK0Vq5llMUfB3rTPYPceWmJiIX3/9FTfffDNGjx6NU6dOAQA++ugj/Prrr4oPkNTPt1HAo5Z2GOutsz8XdQtHZKCyn0puHpmIi7qFobK2Hg+t3OuVRaNyETQboXoOrgRzPXebAQKAIYkhAICdblgIbXcA9MUXXyAlJQW+vr5ITU1FdbVlKrykpAQvvPCC4gMk9dNqJPjoLT9KaimEXmdLf7V/9VdLNBoJf7s6GX4GLXacKMKKLScUfw61K+IMkMdhAORajVeAqX0JfGO2lWCZxa4dSDvYHQAtWbIEb7/9Nv71r39Br2/YAn/MmDFITU2161w///wzLr/8csTFxUGSJKxZs6bJ92+55RZb4bV8mzp16gXPu2zZMnTp0gU+Pj4YOXIkduzYYde4yH5qWgmWVViBvSdLFE9/NRYf5ofHpvcFALz07WEcP1PmkOdRo6raepRZZ/pYA+Q5GAC5VvbZClTVmmHQadwqrT7UuiHi3lPFqHWzDRHtDoDS0tIwfvz48+4PDg5GcXGxXecqLy9HcnIyli1b1uIxU6dOxenTp223//73v62e87PPPsMDDzyAp556CqmpqUhOTkZKSgry8/PtGhvZR017AcmzP6O7Rzj0D/RNIxMwtkcEqmrNeOjzvaj3klSYPPuj10oI8mE/ZU+REG4JgArKalSTyvYmcguM7pEB0LrR6tJuEf4I8dOjqtaMQ6dNrh6OXewOgGJiYpCenn7e/b/++iu6detm17mmTZuGJUuWYPbs2S0eYzQaERMTY7uFhoa2es5XX30Vd955J2699Vb069cPb7/9Nvz8/PDBBx/YNTayj5raYazb177eX/aSJAkvXjUQAUYddmaexfLfMhz6fGrRsAmigYshPEiQjx4hfpZZ/Wy2fHG6hhYY7pP+Aiy/BwfHhwBwv/2A7P74duedd+K+++7DBx98AEmSkJOTg61bt2LhwoV48sknFR/gpk2bEBUVhdDQUFxyySVYsmQJwsPDmz22pqYGO3fuxKJFi2z3aTQaTJ48GVu3bm3xOaqrq221TIBl00eyj1pSYCcKyrH/lAlajYQUJ6xI6Bzqh8dn9MWiVfvwt2/TMLF3FHo4YAXHP348iuyiSjw7qz+MOteusisolxuhMv3laRLD/FBcUYLMwgr0iQly9XC8irv0AGvO0MRQ/JR2Bst+OoYvd+e0+XFjeoTjIesGs65gdwD06KOPwmw2Y9KkSaioqMD48eNhNBqxcOFC3HPPPYoOburUqbjyyivRtWtXHDt2DI899himTZuGrVu3Nttmo6CgAPX19YiOjm5yf3R0NA4fPtzi8yxdupSbOHaQWlJgDemvcKcV6F4/PB7r953GL0cLsHDlHnxx92hFp7C/PZCLl787AsDSe+vhqa77hSGEwIrfTgAAuoSrf6dask/XCH/sOVmCI7mlTvkAQRbp+aX4Zr9l49akzsEuHo39xvWMxMvfHUFBWTUKytq+k3inEF8HjurC7A6AJEnC448/joceegjp6ekoKytDv379EBCg/Kfe66+/3vb/AwcORFJSErp3745NmzZh0qRJij3PokWL8MADD9i+NplMiI+PV+z83kAtM0Dy8vcZAx2b/mpMkiT89aokpLz2M3ZnF+NfvxzHXRO6K3LuovIaPL56n+3rtzcfQ0r/GCRbp5ydbeUfJ7H5yBkYdBo8cOn5O8KTexsUH4I1u3OQ6oZLmt1VXb0ZD67ci5o6Myb0isTYHhGuHpLdkuND8PWCscg1Vdn1uOgg184itykAuvLKK7FixQoEBQXhyiuvbPXYgIAA9O/fH3fddReCg5WNZLt164aIiAikp6c3GwBFRERAq9UiLy+vyf15eXmIiWn504zRaITRyOn8jpBngFxZPJlRUI4DOc5LfzUWF+KLJy/vh4c/34tXvz+CSX2iFNnL46mvDqCgrAY9owLQMzoA6/fl4sGVe7D2nrFO33DyVHElnlt7EADw4KW93GqvEmqbIYkNrQ3MZuG1rV6c6d1fjmNPdjECfXR48aqBbltXN7BzMAbCvWav2lQEHRwcbHtTgoODW73V1dXh7bffxp/+9CfFB3vy5EkUFhYiNrb5T/cGgwFDhw7Fxo0bbfeZzWZs3LgRo0aNUnw81MDf2g6j0oUzQPLsz5geEQh1wf401wztjIt7R6KmzoyFK/egroNLQtfvO42v9+RAq5Hw8jXJeH7WQEQEGJGeX4bXfjii0KjbRgiBR7/Yi9LqOgxOCMEd4+xb8EDuoW9sEHz0GpRU1uJ4AXeEdrS03FK8/v1RAMBTl/dHbLBrU0Lepk0zQMuXL2/2/1ty8OBBDB8+/ILHlZWVNVlRlpGRgd27dyMsLAxhYWF45plncNVVVyEmJgbHjh3Dww8/jB49eiAlJcX2mEmTJmH27NlYsGABAOCBBx7A3LlzMWzYMIwYMQKvv/46ysvLceutt7blpVI7+eqtKbBa1wVAa/daAqDLnJj+akySJCy9MgmXvrYZe06W4J2fj2P+xT3ada7Csmo8uWY/AODuCd1tKa8XZg/AvI924l8/H0dK/xhbM0JH+++ObPxytABGnQYvX5PsVst0qe30Wg2SOoVgx4kipGaddUhBP1nU1ls+KNXUmzGpTxSuGtLJ1UPyOg5pN9u7d29s2bLlgsf98ccfGDx4MAYPHgzAErwMHjwYixcvhlarxd69e3HFFVegV69euP322zF06FD88ssvTdJVx44dQ0FBge3r6667Di+//DIWL16MQYMGYffu3diwYcN5hdGkLHkGyFUd4Y+dKcOh0yboNBKm9Hfdex0T7IOnL+8PAHjjh6NIyy1t13kWf3kAheU16BMTiHsmNQRRU/rHYPbgTjALYOHKPahyQsCZXVSB59dZUl8PpfRG90j+UfRkchpsF+uAHOqdzcew71QJgnx0eOFK9019uTOH7GKm1WqRnJx8weMmTpwIIVrePO7bb7+94DlOnDhx3n0LFiywzQiRc/i6eB+g9dbZn7E9IxDi59r2DFcO6YRv9p/GD4fysXDlHqz682jotW3/rLF2bw7W7TsNnTX1de6y96cu74ff0gtw/Ew5XvkuDY/P6Kf0S7AxmwUe+WIvymvqMSwxFLeO6eqw5yJ1GJIQAsD99nRxJ4dOm/DGRkvq65mZ/REd5OPiEXknh8wAkffx07s2AFrngtVfLZEkCS/MHohgXz32nSrB25uOtfmxZ0obUl9/vrgHBnQ6v6gwxM+ApVcOBAC892sG/jhRpMzAm/HJjixsOVYIH70Gf2PqyyvIM0BH88tgqqp18Wg8j5z6qq0XuLRfNGYNYurLVRgAkSL8jPIyeOenwNLzS3E4txR6rYQp/dSxd0lUkA+eucKSCnvzx6Nt2iJeCIEn1uzD2Ypa9I0NwoJW6ocm9Y3GVUM6Q1hTYY4oPs8qrMDS9YcAAI9M7YOuEe7Tn4jaLyLAiIQwPwgB7M4qdvVwPM4/fzqGAzkmhPjp8fzsAUx9uRADIFKEbRm8C2aA1u21bCA2tkcEgv30FzjaeWYOisOUftGorRd48H97Ltgo8Ks9Ofj2QB50GgmvXJMMg671f56LL++H6CAjThRW4G/fpik5dJjNAg99vgcVNfUY0TUMc0d1UfT8pG5DbcvhmQZT0oGcEvz9R0vq69mZAxAVyNSXKzEAIkX4WzdCdMUy+IbeX3FOf+7WSJKE52cPRKifHgdPm7Dsp/N76MnyTVVY/OUBAMC9k3qiX9yF2xAE++rx4lVJAIDlWzKw/XihMgMH8OHWE9ieUQRfvRYvX53M/WC8DOuAlFdTZ8aD/9uDOrPA1P4xuNzBvQrpwhgAkSJ8bTNAzk2BHc0rxZG8Mui1Ei7tp76VfpGBRjwzcwAA4B8/puNATsl5xwgh8NjqfSiprMWATkG4e2Lbd5G+uHcUrh1mSYU99PleRVKQJwrK8dcNlhmlRdP72LqEk/cYbN1eYXe2ZUNE6rh//HgUh3NLEeZvwBKmvlSBARApwlUzQHLx8/iekQj2VU/6q7HLk2IxbUAM6syWVFhNXdNU2Opdp/DDoXzotZZVX/asGAOAJy7rh9hgH2QVVeCv37Tc864t5NRXZW09RnULx80jEzt0PnJPfWIC4WfQorSqDulnylw9HLe3/1QJllkXQzw3cwAiAth5QA0YAJEiXLUMfp11+fsMFU8nS5KE52YNQJi/AYdzS/EPaw0AAOSWVOHpryypr/sn92pXB+4gHz3+ak2F/XtrJrYea38qbPmWE/j9xFn4G7R46eokpr68lE6rQXLnEABAKtNgHVJdV48H/7cH9WaBGUmxqv5d5W0YAJEibBshOjEFdiSvFEfzy2DQajBZhemvxiICjHjOmgpbtukY9p0sgRACi1bthamqDkmdg/F/49vfXmJ8r0jcMCIBAPDQ53va1ZPt+JkyvLTBMoP02Iy+iA9j6subDUkMAcA6oI56c+NRpOWVItzfgGetK0NJHRgAkSL8rK0wauvFeSkeR5FbX4zvFYkgH3WmvxqTP/3VmwUWrtyD/+zIwk9pZ2DQavDKNcnQ2Zn6Otdj0/ugU4gvTp6txNJvDtn1WHlM1XVmjO0RgRutwRR5L7nNCleCtd+e7GK8ZU19LZk1AOFMfamKQ3aCJu8jp8AASx3QhZZwd5QQAuv2WlZ/XeZGU8rPzRyA7ccLkZZXisdXWzY8/ItCndUDramwm9/fjo+3ZWF8z0gMsvYQu5CVO08iNasYAUb37khNypELoY+dKUdxRY0iO6wLIVBnFnbXubmjqtp6LFy5B2YBXJEch2kq2KSVmmIARIow6DTQayXU1gtU1NYhGI6dkUnPL8OxM+Uw6DSY1DfKoc+lpDB/A5bMGoi7Pt4JABgUH4I7xynXXmJszwjcfFECPt6WhXkf7bT78U/M6IvOoUx9keVntVuEP44XlGNXdjEu7t2xf2dCCFz3zjZkFVVg1Z9HIy7Eszufv/7DURzNL0NEgNG2KSqpi+eH4eQ0vtZ2GOXVji+EPppvWZkyIC4IgW6Q/mps6oAY3DK6C+LDfPGyAqmvcy2a1hdJnYOhkWDX7YrkOFw3PF7RsZB7k2eBlCiEPpBjwo4TRcg1VeHRVfta7QPp7lKzzuLdny2prxdmD0Cov2v7E1LzOANEivE36mCqqnPKUvgzpdUA4LZNBJ++oj+edtCnQn+jDl8tGOuQc5N3GZIYgi9STypSByRvWQEAPx85g89+z8b1Hlhr1jj1NXtwJ0zpr472PHQ+zgCRYpy5GWJ+aRUAICqQRYVEjiIXQu/OKkZ9BzZEtNTsWQKgi7qFAQCWrDuEk2crOj5IlXn1+yM4fqYcUYFGPHV5P1cPh1rBAIgU48zNEOUZoEgGQEQO0ys6EAFGHcpr6nEkr7Td5zmQY0JWUQV89Br8a84wDE0MRVl1HR79wrNSYTszi/CvX44DAJZeOVCRwnFyHAZApBjnzgBZAiA2EyRyHK1Gsq0k7Mh+QPKWFZP6RCPQR4+/XZ0EH70Gv6YX4D87spQYqstV1tRj4cq9EAK4emhnTOqr7r3JiAEQKcjfibtBcwaIyDnkxqjtrQMSQjRqWGxZCt4tMgAPp/QBADy/7hCyi9w/Ffa3b9OQUVCOmCAfPHkZU1/ugAEQKcbPiSmwfAZARE4xONFSB7Qrq7hdj993qgTZRZXw1WubLKW/ZXQXjOgShoqaejz8+V63brq6I6MIy7dkAACWXjVQtX0JqSkGQKQYPyelwOrNAoVlcgqMARCRIw2JtwRAGQXlKCqvsfvxcvHzJX2jmmyYqtFIeOnqJPjqtdh6vBAfb89UZsBOVlFTh4c+3wMhgOuGxXd4vyRyHgZApBg5AHL0DFBheTXMwrJ3DbeWJ3KsYD89ekQFALB/PyAhhK3+57JmdkLuEuGPR6dZUmFL1x9GZmF5B0frfC9tSENmYQXign3w+GV9XT0csgMDIFKMrzUF5uiNEPNNltmfMH8jtOxWTuRw7a0D2nOyBKeKK+Fn0GJiCzMjf7ooERd1C0NlbT0ecrNU2NZjhVix5QQA4MWrktyiJyE1YABEipGLoCtrHZsCO8P0F5FTtbcxqtyvb1Lf6Cbpr8Y0Ggl/uzoZfgYtdmQU4d9bT3RorM5SXl2Hh7/YAwC4YUQCxveKdPGIyF4MgEgxtmXwDp4BOmNiATSRMw21FkLvyS5BXb25TY9pvPnhjAs0Ao0P88Oi6Zb00V83HEZGgfpTYS9+cxjZRZXoFOKLx2cw9eWOGACRYvyNlhSYo5fBcwaIyLm6RwYgyEeHytp6HM5t24aIu7KLkVNSBX+DFhN7X3h25KYRCRjTIxxVtWY8tHJPh3aedrTf0gvw0TZL0fZLVychwMiuUu6IARApxs+2D5BjU2D5JmsbjCAGQETOoNFIGGRnGmy9dfZncr9o+OibT3+d+xx/vSoJ/gYt/sg8i+W/ZbR/wA5UWlWLhz/fCwC4+aIEjOkR4eIRUXsxACLFyPsAOWsGKJIrwIicxlYI3YaVYGazwHpr89PpF0h/NdY51A9PWDcR/Nu3aTh2psz+gTrYC+sP41RxJTqH+mLRNKa+3BkDIFKM82aArCkwN+0ET+SO5Dqg1DZsiNg4/TXBzuLg64fHY1zPCFTXmbFQZamwn4+cwX+trTv+dnWyLe1P7onvHinGz0mtMGwzQKwBInKaQfEhkCQgq6gCZ0qrW/33Jxc/X9rG9FdjkmRJhaW89jN2ZRXjiTX70C8uuM2PH909HN0jA+x6zrYwVdXi0S8sqa9bRnfBqO7hij8HORcDIFKMM1phCCEaZoAYABE5TaCPHr2iApGWV4rUrLNI6R/T7HGN018zkuLa9VxxIb548rJ+ePiLvfjvjmwA2W1+bLi/Ad/+ZTwiFE6RP7/2EHJKqpAY7oeHp/ZW9NzkGgyASDHOaIVRXlOPylpLgMUZICLnGpIYcsEAKDXrLHJNVQg06jCuZ/sLhK8Z1hl5piocPG1q82P2WjdeXPzlfvzzpqHtfu5z/ZSWj8/+yIYkAS9dlWT7sEfuje8iKUYOgKpqzag3C4fs0iyvAAsw6vhLiMjJhiSE4r87srErs7jFY9Z2IP3VmCRJuGdST7ses/9UCWYt+w3r9+Vi7d4cXNbOGajGSiprseiLfQCAW0d3xchuTH15ChZBk2IaByTyLI3S2AWeyHWGyBsinixGbTMbIjZNf7V99ZdSBnQKxp8v7gEAeHLNfpyx/r7oiOfWHkSuqQpdI/zxUApTX56EARApxkevgWSd9HHUSrAzDICIXKZbhD9C/PSorjPjYM75qak/Ms8iv7QagT46jO1A+qsjFlzcA31jg3C2ohZPrNkHIdq/imzjoTx8vvMkJAn429VJLbbzIPfk0gDo559/xuWXX464uDhIkoQ1a9bYvldbW4tHHnkEAwcOhL+/P+Li4jBnzhzk5OS0es6nn34akiQ1ufXp08fBr4QAy5S1n3XKu8JB7TA4A0TkOpIkYXB8CIDmN0SUZ3+m9IuBUeeaYMGg0+CVa5Kh00j49kAevtrT+t+MlpRU1GLRKkvq646xXTGsS5iSwyQVcGkAVF5ejuTkZCxbtuy871VUVCA1NRVPPvkkUlNTsWrVKqSlpeGKK6644Hn79++P06dP226//vqrI4ZPzfBzcDsMeQaIK8CIXKOl/YDqm6S/mi+QdpZ+cUG411o/tPjLA7baQXs88/UB5JdWo1ukPx6cwtSXJ3JpFem0adMwbdq0Zr8XHByM77//vsl9//jHPzBixAhkZWUhISGhxfPqdDrExLj2H6C3cvRmiPmlll9knAEicg1bZ/hzdoT+40RRQ/qrh+s7o989sTu+O5iL/adMeGz1PvxrzjBIUtsWZnx3IBerdp2CRgJevia5Q8XcpF5uVQNUUlICSZIQEhLS6nFHjx5FXFwcunXrhptuuglZWVmtHl9dXQ2TydTkRu3j6HYYDTNA3AWayBWS40OgkYBTxZXIazSzss46+5PSPwYGnev/tOi1Grx8TTL0Wgk/HMrH6l2n2vS4s+U1eGz1fgDAvPHdbQEfeR7X/5S2UVVVFR555BHccMMNCAoKavG4kSNHYsWKFdiwYQPeeustZGRkYNy4cSgtbbmD8dKlSxEcHGy7xcfHO+IleAVH7wbNFBiRa/kbdegdY/kdLM8CWdJfuQBcs/qrJX1ignD/5F4AgKe/OtAkYGvJU18dQEFZNXpGBeD+yfYtwyf34hYBUG1tLa699loIIfDWW2+1euy0adNwzTXXICkpCSkpKVi/fj2Ki4vxv//9r8XHLFq0CCUlJbZbdnbbdx2lphydAuMqMCLXG5oYAqChEHpHRhEKyqoR7KvHmO7q6o7+f+O7IalzMExVdVi0qvVVYRv2n8ZXe3Kg1UhMfXkB1QdAcvCTmZmJ77//vtXZn+aEhISgV69eSE9Pb/EYo9GIoKCgJjdqH0fOANXWm1FYXgOAM0BErmSrA7IWQq/bZ1lpldI/WhXpr8Z0WsuqMINWgx8P5+PznSebPa6wrBqPW1Nfd03ohmTrajfyXOr6ST2HHPwcPXoUP/zwA8LD7d+Bs6ysDMeOHUNsrHqmZT2Zv60GSPkZoMIyS/Cj00gI9TMofn4iahs5ANp3sgSVNfXYsF9Of3V852VH6BkdiL9cakmFPfv1QZwuqTzvmMVfHUBheQ16RwfaVpCRZ3NpAFRWVobdu3dj9+7dAICMjAzs3r0bWVlZqK2txdVXX40//vgDn3zyCerr65Gbm4vc3FzU1NTYzjFp0iT84x//sH29cOFCbN68GSdOnMCWLVswe/ZsaLVa3HDDDc5+eV7J14EzQPIKsIgAIzQOaLNBRG2TGO6HMH8DaurN+OC3DBSU1SDET4/RKu6Qfue4rhgUH4LS6jo88kXTVNi6vaexbu9paDUSXrk22WV7GJFzuTQA+uOPPzB48GAMHjwYAPDAAw9g8ODBWLx4MU6dOoWvvvoKJ0+exKBBgxAbG2u7bdmyxXaOY8eOoaCgwPb1yZMnccMNN6B379649tprER4ejm3btiEy0vXLMr2BI1NgrP8hUgdJkmyzQP/8yVJekNIvBnqtepMKOuuqMINOg5+PnMH//rDUehaUVePJLy2pr/kTu2NAp2BXDpOcyKX7AE2cOLHVgrS2bGF+4sSJJl9/+umnHR0WdYCfA1Ng+VwBRqQaQxJD8MOhPJRbP+yoafVXS3pEBWDhlF54Yf1hPLf2EMb2jMSStQdRVF6DPjGBWHAJU1/eRL3hOrkl2wyQA1ph5Js4A0SkFo33xwn102OUitNfjd0+thuGJISgrLoO17+7Fd/sz4XOmvpSWwE3ORbfbVKUI1thnCmz1ABxBojI9ZI6B0NrrcWbOkDd6a/G5CXuRp0G2UWWYuh7LumJ/nFMfXkb9/iJJbchN0Mtd0QKjDNARKrhZ9BhhLVB6OzBnV08Gvt0iwzAw1MtTbIHdArCny/u7uIRkSu4tAaIPI+/0RIAVTpkBkgOgNgGg0gN/n7jYOQUVyKpc4irh2K328Z0Qd/YQPSLDXKb2StSFgMgUpSvA3uBcQaISF0iAoyICHDPf4+SJGG0ynatJudi2EuK8ndQKwwhhG0GiDVARETUUQyASFGO2gjRVFmHmjozAM4AERFRxzEAIkX5OSgFJq8AC/LRsUEhERF1GAMgUlTjFFhbNrJsK7n+JyqIBdBERNRxDIBIUXIKzCyAamvKSgm2FWBuWnBJRETqwgCIFCWnwABl02ANM0AMgIiIqOMYAJGitBoJRut28uXVyq0E4wwQEREpiQEQKc7f2g6jslbJGSBrGwzOABERkQIYAJHifOV2GArOAMmd4LkEnoiIlMAAiBTniHYYZ0rlTRC5CoyIiDqOARApzhHtMDgDRERESmIARIqT9wJSqiN8dV09SiprAbANBhERKYMBECnOz6BsCkxOfxm0GgT76hU5JxEReTcGQKQ4OQVWrnAAFBlohCRJipyTiIi8GwMgUpy/bQZImRQY63+IiEhpDIBIcb62GiDlZ4CIiIiUwACIFOdvTYEpVQOUb1sCzwCIiIiUwQCIFGebAVJoI0TOABERkdIYAJHi5BqgCoVaYZwptbbB4CaIRESkEAZApDg/hVNgnAEiIiKlMQAixfkZlU2BsQaIiIiUxgCIFGfbCFGBFJjZLDgDREREimMARIqTU2BKzAAVV9aiziwAABEBDICIiEgZDIBIcUq2wsi3FkCH+ulh0PHHlYiIlMG/KKQ4PwU3Qjxjq//hCjAiIlIOAyBSnJKrwPJN1gAoiOkvIiJSDgMgUpw8A1RTb0ZtvblD5zpTZi2AZv0PEREpiAEQKU6eAQKAig7OAskzQJGcASIiIgW5NAD6+eefcfnllyMuLg6SJGHNmjVNvi+EwOLFixEbGwtfX19MnjwZR48eveB5ly1bhi5dusDHxwcjR47Ejh07HPQKqDkGnQY6jQQAqOhgR3jOABERkSO4NAAqLy9HcnIyli1b1uz3X3rpJbz55pt4++23sX37dvj7+yMlJQVVVVUtnvOzzz7DAw88gKeeegqpqalITk5GSkoK8vPzHfUyqBlyGqzjM0DWNhhBLIImIiLluDQAmjZtGpYsWYLZs2ef9z0hBF5//XU88cQTmDlzJpKSkvDhhx8iJyfnvJmixl599VXceeeduPXWW9GvXz+8/fbb8PPzwwcffODAV0LnUqoQmjNARETkCKqtAcrIyEBubi4mT55suy84OBgjR47E1q1bm31MTU0Ndu7c2eQxGo0GkydPbvEx5BhKtcM4w1VgRETkALoLH+Iaubm5AIDo6Ogm90dHR9u+d66CggLU19c3+5jDhw+3+FzV1dWorq62fW0ymdo7bLLyU6AjfGVNPUqtARTbYBARkZJUOwPkTEuXLkVwcLDtFh8f7+ohuT05BVZR3f4ASN4E0UevQaBRtbE6ERG5IdUGQDExMQCAvLy8Jvfn5eXZvneuiIgIaLVaux4DAIsWLUJJSYntlp2d3cHRU0MRdPtTYHIbjMhAIyRJUmRcREREgIoDoK5duyImJgYbN2603WcymbB9+3aMGjWq2ccYDAYMHTq0yWPMZjM2btzY4mMAwGg0IigoqMmNOkaJVWBsg0FERI7i0rxCWVkZ0tPTbV9nZGRg9+7dCAsLQ0JCAu6//34sWbIEPXv2RNeuXfHkk08iLi4Os2bNsj1m0qRJmD17NhYsWAAAeOCBBzB37lwMGzYMI0aMwOuvv47y8nLceuutzn55Xs2WAutAAJRfyhVgRETkGC4NgP744w9cfPHFtq8feOABAMDcuXOxYsUKPPzwwygvL8e8efNQXFyMsWPHYsOGDfDxaZgROHbsGAoKCmxfX3fddThz5gwWL16M3NxcDBo0CBs2bDivMJocS4kUmG0GiCvAiIhIYS4NgCZOnAghRIvflyQJzz77LJ599tkWjzlx4sR59y1YsMA2I0SuocwMkHUTRK4AIyIiham2Bojcm5IzQFwCT0RESmMARA6hRBF0PougiYjIQRgAkUMokQLjDBARETkKAyByCH9jx1Jg9WaBgjJ5BogBEBERKYsBEDmEr75jKbCi8hqYBSBJQJi/QcmhERERMQAix+hoKwx5BVi4vxE6LX9MiYhIWfzLQg4hd4OvqG1fCoz1P0RE5EgMgMghbKvA2j0DxPofIiJyHAZA5BD+HVwFxhkgIiJyJAZA5BC+1hmgytp6mM0t7/bdkjOcASIiIgdiAEQOIc8AAZYgyF5sg0FERI7EAIgcwkevgY/e8uOVUVBu9+MbUmDcBZqIiJTHAIgcQpIkTOgVCQD4Zv9pux+fz07wRETkQAyAyGFmJMUBANbtPQ0h7KsDss0ABTAAIiIi5TEAIoeZ1CcKRp0GJworcCDH1ObHlVXX2VaPcRUYERE5AgMgchh/ow6X9IkCAKzb1/Y0mDz742/Qwt+ou8DRRERE9mMARA41IykWgH1psHyTdQVYEAugiYjIMRgAkUNd0icKPnoNsooqsP9U29JgZ8pY/0NERI7FAIgcys+gw6Q+0QCAtfty2vSYfJM1AOIKMCIichAGQORw9qbBOANERESOxgCIHO7i3lHw1Wtx8mwl9p0queDx8gwQ9wAiIiJHYQBEDudr0OKSvtbVYHsvvBpMboPBGSAiInIUBkDkFJcNtKTB1rYhDWZrhMpVYERE5CAMgMgpJvaOgp9Bi1PFldhzsvU0GDvBExGRozEAIqfwNWgxqa9lNdi6vS2vBqutN6OoogYAd4EmIiLHYQBETjNj4IVXgxWW1UAIQKuREOZncObwiIjIizAAIqeZ2DsS/gYtckqqsCu7uNlj5PRXRIABGo3kxNEREZE3YQBETuOj12JyPzkN1vxqMHkFWFQgC6CJiMhxGACRU8lpsPX7TsNsPj8NJs8Asf6HiIgciQEQOdX4XpEIMOpwuoU0WD5XgBERkRMwACKn8tFrMbmVTRE5A0RERM7AAIicbkZSHIDm02ANNUAMgIiIyHEYAJHTjesZgUCjDrmmKqRmnW3yPc4AERGRM6g+AOrSpQskSTrvNn/+/GaPX7FixXnH+vhwRZGa+Oi1uNS6GmztOWmwfFsAxPeMiIgcR/UB0O+//47Tp0/bbt9//z0A4JprrmnxMUFBQU0ek5mZ6azhUhvNSDp/NZgQgkXQRETkFDpXD+BCIiMjm3z94osvonv37pgwYUKLj5EkCTExMY4eGnXA2J4RCPTRIb+0Gn9knsWIrmEwVdWhps4MgCkwIiJyLNXPADVWU1ODjz/+GLfddhskqeVdgsvKypCYmIj4+HjMnDkTBw4ccOIoqS2MOi2m9LMEqXJvsDPWAuggHx189FqXjY2IiDyfWwVAa9asQXFxMW655ZYWj+nduzc++OADfPnll/j4449hNpsxevRonDx5ssXHVFdXw2QyNbmR410mp8H256LeLBrV/3D2h4iIHMutAqD3338f06ZNQ1xcXIvHjBo1CnPmzMGgQYMwYcIErFq1CpGRkXjnnXdafMzSpUsRHBxsu8XHxzti+HSOMT0iEOSjw5nSavxxosi2AoxtMIiIyNHcJgDKzMzEDz/8gDvuuMOux+n1egwePBjp6ektHrNo0SKUlJTYbtnZ2R0dLrWBQadBSn9rGmzfaS6BJyIip3GbAGj58uWIiorCjBkz7HpcfX099u3bh9jY2BaPMRqNCAoKanIj55huWw2Wi9Ml3ASRiIicwy0CILPZjOXLl2Pu3LnQ6ZouXJszZw4WLVpk+/rZZ5/Fd999h+PHjyM1NRU333wzMjMz7Z45IucY0z0Cwb56FJRVY8P+XACcASIiIsdT/TJ4APjhhx+QlZWF22677bzvZWVlQaNpiOPOnj2LO++8E7m5uQgNDcXQoUOxZcsW9OvXz5lDpjaypMGi8b8/TuJUcSUAICqIARARETmWJIQQFz7Mu5hMJgQHB6OkpITpMCfYfOQM5n6ww/b1x7ePxNieES4cERERuSN7/n67RQqMPNvo7uEI8dPbvuYMEBERORoDIHI5vVaDqf0bdu6ODGAAREREjsUAiFRB7g1m0GmazAYRERE5glsUQZPnG909AneO64r4ML9W25wQEREpgQEQqYJWI+HxGVypR0REzsEUGBEREXkdBkBERETkdRgAERERkddhAERERERehwEQEREReR0GQEREROR1GAARERGR12EARERERF6HARARERF5HQZARERE5HUYABEREZHXYQBEREREXocBEBEREXkdBkBERETkdXSuHoAaCSEAACaTycUjISIioraS/27Lf8dbwwCoGaWlpQCA+Ph4F4+EiIiI7FVaWorg4OBWj5FEW8IkL2M2m5GTk4PAwEBIkuTq4aiGyWRCfHw8srOzERQU5OrhuDVeS8/F91Y5vJbK8ZZrKYRAaWkp4uLioNG0XuXDGaBmaDQadO7c2dXDUK2goCCP/gfkTLyWnovvrXJ4LZXjDdfyQjM/MhZBExERkddhAERERERehwEQtZnRaMRTTz0Fo9Ho6qG4PV5Lz8X3Vjm8lsrhtTwfi6CJiIjI63AGiIiIiLwOAyAiIiLyOgyAiIiIyOswACIiIiKvwwCIbOQWIERE5F7q6upcPQS3wwCIkJOTg1GjRmHhwoWoqalx9XDcWkFBAbZs2YLjx4+7eiiksLKyMpSUlABoW6NFalleXh5ef/11rFq1CkeOHAHAa9peOTk5GDFiBBYvXuzqobgdBkBebuHChUhMTERkZCSeeuopGAwGVw/JbS1atAh9+/bF/fffjwEDBuC1115DYWGhq4dFCnj66acxYMAArF69GgDYI7ADFi9ejO7du2Pt2rVYsGAB5s6di4MHD0KSJAZBdvrLX/6CLl26ICYmBgsWLHD1cNwOe4F5qYKCAiQlJUEIgU2bNmHMmDGuHpLbysnJwX333YcTJ07g888/R9euXfHee+/hvffeQ48ePXD55Ze7eojUTkVFRXj44Yexa9cuAMD69esxZswY9OzZE0IIBkJ2+uijj7Bu3Tp8+eWXmDRpEjZu3IjHHnsMW7duRb9+/Xg92ygrKwujRo2Cj48Pfv31V4wYMcLVQ3JLDIC8VEREBAYPHoyamhqMGTMGu3btwvvvv4/g4GD0798fkydPRlRUlKuHqVqN//gdOnQIkiThzTffxKhRowAAzz77LD788EPk5eWddzypW+P3qq6uDrGxsZg9ezZ8fX3xpz/9Cd9++y26dOkCvV7v4pGqn3wt5f9u2LABkZGRmDRpEgDY/tv4Dzj/rVyYTqdDp06d0L17d4wYMQKpqan49NNPERMTg6SkJIwdOxY+Pj6uHqbqcSdoLyH/Uqmrq4NOZ4l7Dx8+jIEDB2LYsGE4deoURo0ahfz8fKSnp6N///5Yv349NBpmSc9VU1MDjUZju475+fk4fPgwxo8fDwAwm82QJAljx47F3LlzMW/ePFcOl+xQU1MDIYStXUBdXR2KiopsHwZuvfVWHDlyBK+//jqGDx/uyqGq3rnXsqqqCo8++ih+//13/OMf/0BCQgLmzZuHrVu34qKLLsLIkSOxcOFCaLVaF49cfZr7/b1hwwZMnz4dl156KQ4fPozk5GScOHECeXl5uPLKK/HPf/6TgeQF8K+bF3jllVdwxx13AIDtHw8A9OnTB48//jjKysqwcuVKfPzxx/jpp5/wz3/+ExkZGXjmmWdcNWTVWrJkCaZOnYqZM2fi73//OwoLCxEVFdUk+NFoNMjPz8f+/fsxcOBAF4+Y2urpp5/G2LFjMXPmTLz77rsoKiqCTqdDVFQUzGYzAMv7f+rUKaxZswbFxcUAWLzbnHOvZWFhIXx8fHDFFVcgNDQUjzzyCKKiolBcXIx33nkH3bp1wzvvvIO77roLAGzXm4C///3vePrppwFYfn/LP2/jxo3D//3f/6GoqAiff/45PvvsM+zduxePP/44tm7dirffftuFo3YTgjzWgQMHxOWXXy78/f1FdHS0WLlypRBCiLq6OtsxxcXF4ueffxa1tbWivr5eCCFERUWFuPPOO8WMGTNEZWWlS8auNjt37hTDhg0T/fv3F++//7647rrrxODBg8Vf/vKXZo//+uuvRc+ePUVVVZWTR0r2qq2tFX/6059Ejx49xL///W9xww03iP79+4sZM2Y0OU7+d/Pcc8+JPn36iG+++cb2PbPZ7NQxq1VL13L69Om2Y+rr68U777wjZsyYISoqKmz3L1++XERHR4v8/HxXDF11du/eLVJSUoQkSWLgwIFi48aNQoimv7+PHDkitm7dKurr622/vwsLC0VKSopYsGBBk2PpfJwB8mBbtmyBJEn44IMPkJKSgjfeeAM1NTXQarW2T1jBwcEYN24cdDodNBoNzGYzfH19cejQIRgMBnYOhmX583//+1/06dMHv/32G2677TZ8+umnmDFjBtLT020zAY2lpqZi+PDhtuv322+/YdWqVU4eObVFdnY2fv/9d7z66quYM2cO/vOf/+C1117Djz/+iNdee812nJxOePzxx2E0GvH5558jIyMDX375JZYtW+aq4atKS9fyp59+sl1LjUaDw4cPIyoqCr6+vk0eGx0dzdkfq40bN8JoNGLFihWIj4/HihUrUFdX1+T3d48ePXDRRRdBo9HYfn+HhYXhxIkTtt/11DIGQB5IWKdIr7vuOixcuBDXXnstZs+ejdLSUrz66qutPlaj0WDLli2oq6vDrbfeyhwyLNeza9euuPvuuxEcHGzbcCw4OBhpaWkICgo67zHffvstJk2ahFOnTmH69OmYMGECN5pUqdraWqSlpSE5Odl236WXXoonn3wSzz77LLKysgBY/m3U19dDkiQ8/vjj+OqrrzBx4kRcffXVTINZtfVa5ubmoqioCFu2bAEAHDlyBJs2bcIll1yC6Ohol4xdbW688UY8+OCDmDNnDqZMmYIjR47gk08+AdAQjJ/7+1mj0WDjxo0ICgrC3LlznT5md8MAyAPJ/ygCAwMxbtw4AJZ88aRJk/DJJ58gMzPT9stclp6ejm+++QYLFizAtGnTMGTIEEyZMsUl41ebwMBA/N///R9Gjx4NALbC8JKSEgwaNOi8QvEjR47g0KFD+Pzzz9GtWzcYDAbk5eXxF5JK1dfXIzk5GZ999lmT++fPn4+wsDC88cYbtuO0Wi0yMzPx448/oqCgAJMmTUJeXh7uueceVwxddS50LV955RXb17m5ubj88ssxa9YsDBs2DLGxsXjuuedcMWxViomJsdUWXnXVVUhISMDKlSuRl5cHSZKazJQdOnQImzdvxn333YdrrrkGY8eOZZF+GzAA8gJCCISHh+OKK65ASEgIli5dCgBNpkczMjLwwQcf4MCBA/j++++xbNkypr+shBBNrpUcYKampmLIkCG2Y2THjx9HcXExTCYTNm/ejDVr1iA8PNy5gyabC83OJCQkoHfv3ti+fTtOnDgBwFKEGxQUhLvvvhuff/45qqqqbD8Db7zxBtasWYPt27fjgw8+QFhYmKNfgmp09FquXr0aFRUVGDNmDN5//328/vrrGDFiBDZt2oSPP/4YAQEBTngV6tDWWUOz2YzOnTtj9uzZKCoqwvvvvw8ATT547dmzB88//zxSU1PxzTff4NVXX+U2DW3hsuoj6pDa2lohhLAVvjX3vXO/rqmpES+++KLo3bu3+OWXX4QQQvz2229CCCGqq6tFVlaWI4esWvZcS/mY4uJiER4eLjZv3mz73okTJ4QQQuTn54vvvvvOUcMlOxQXFwuTyWQrUm78Hjd+b//73/+KpKQk8de//rXJ4999910xYMAAkZmZabuvtLTUwaNWJ6WupfzvxJu19Vo2/rqiokL83//9n5gwYYLYs2ePEEKIHTt2CCGEKCsrE0eOHHHG0D0KZ4Dc0H333YcZM2YAaPopQFg/UchLJeWiQ/lrvV6PGTNmoH///li0aBGmT5+OsWPH4uDBgzAYDIiPj3f+i3Exe6+lfMzGjRsREhKC8ePH49SpU7j22msxfPhw5OXlITIyEpdeeqmTXwk1JoTA/fffjwkTJmDq1KmYM2cOSktLodFoUFtbC8Dy3tbX1+OTTz7B9ddfj9GjR2P16tVYu3at7TwFBQUICQlBp06dbPd50ywFoPy17Ny5s6teisu19VoKIfDvf//b9rW8OOW6666DTqfDCy+8gGnTpmHkyJHIycmBv78/evbs6cqX5p5cFnqR3Q4ePCimT58uEhIShCRJ4uOPPxZCnD9z8a9//UtER0eLiy66SJw6darJ93Jzc8WYMWOEJEniyiuvbPLJ1pt09Fo+//zz4uqrrxbPP/+88PX1FZdeeqnXzqCpzdatW0VycrK46KKLxLp168Qzzzwj+vTpI6677romx7377rsiKipKTJkyRdTU1IhDhw6J2267Teh0OnH33XeLBQsWiODgYPH3v/9dCOGdS915LZVj77WcPn26yMvLa/K9vLw80b9/fyFJkpg9ezZn0zqIAZAb+eKLL8Ttt98ufvzxR3H//feLmJgYUVNT0+SYr7/+WgwePFi899575+0BsWfPHtGzZ0/Ro0cP8euvvzpz6KrT0Ws5YsQIIUmS6Nu3r/j222+dOXRqRV1dnXj44YfFDTfc0CRV9dlnn4muXbuK3NxcIYQQH374oYiPjxfvv//+eSmHl19+WcybN0+kpKTY9l7xRryWymnPtTz3d87WrVtFWFiY6NOnj9f//lYKAyAVO3c2oqCgQBw8eFAIIURGRoaIi4sTjz76qBCi6eZYZWVlzZ6voqJCfPnllw4arbopeS3LysrEY489Zps1Itdq/N7W1dWJb775pkltlhBCrFixQvTr10+YTCbbfY3/XwjvnJU4F6+lcpS6lrKysjLx0UcfOWawXoq9wFTq2WefRUZGBrp164Y///nP560iqq+vx1tvvYUHHngA6enpSEhIsLVhaI7w4gaDSl9LUo+2vLdarRavvvoqVq1ahV9++QXA+funEK+lkpS+lt78+9uR+BteZbKzszF06FB8/vnn8Pf3xz//+U9MnToVn3/+OYCG4lytVovrr78eycnJuO+++wCg1T/Y3viPx1HXklzvQu+tvEeK/HP/888/Y+zYsV757+BCeC2V46hryWvtIK6cfqLzrVixQgwaNEgUFxcLISzTnldccYUYO3as2L17txCi6TLJr7/+WkiSZJta/fbbb0VaWprzB65CvJaeqy3vbePedgkJCeKHH36wPV5OfxKvpZJ4Ld0LP+aqzIkTJ6DX6+Hv7w8A8Pf3x4MPPgij0Yi//vWvAJp2BJ40aRKuu+46zJ07FxdddBFmzZrVbG8qb8Rr6bna8t7Ks3i//PILNBoNRo8ejYMHD+Liiy/G0KFDkZub67LxqwmvpXJ4Ld0LAyCVqaqqgk6nQ35+vu2+8ePHY9q0aTh06BB++OEHAA3pm1OnTqGwsBCZmZkYOHAg8vLyMGLECJeMXW14LT1XW99bANi3bx9iYmKwePFiJCUlIS4uDnl5eYiJiXHF0FWH11I5vJbuhQGQSsi54blz52Lbtm3YsWNHk+9PnjwZRqMRO3fuBGD5FJGWloYbb7wROTk52LdvH/71r38hMDDQ6WNXG15Lz2XvewsA69evx/bt27F9+3bs2LEDn3zyCd9b8FoqidfSPXEVmAuIZir66+rqoNPpAADXXnst0tPT8d133yEiIsJ2zEUXXYQRI0bgzTffBACUlpbi+PHjTTovexteS8+lxHtrNpvxv//9D35+frjiiiucOn414bVUDq+l5+AMkBPU1tbi5ZdfxurVqwE0reiXO7LrdDrU1NQgPT0dL7/8Mg4fPozXXnsNJSUlACz/wIxGI0JDQ22PDQwM9Lo/2LyWnssR761Go8H111/vdX9keC2Vw2vpwVxUfO011q9fL/r27SskSRI33XSTrZ3CuRuFvfHGG8LPz8/WQPDdd98VPXr0ECkpKeLLL78Uf/nLX0RsbKyt+Z034rX0XHxvlcNrqRxeS8/GAMiBysrKxB133CHuvfdesXTpUjFs2DDx1ltvNTmmurpa3HXXXSIqKkp89NFHTXYP/frrr8X06dPFqFGjxLBhw8S2bduc/RJUg9fSc/G9VQ6vpXJ4LT0fa4AcSAiBrVu3Ijw8HL1798bVV1+NmpoaLFmyBElJSbZj0tPTER0djaCgIAA4bxfivLw8REdHu+Q1qAWvpefie6scXkvl8Fp6PgZACvr8888REhKC/v37IzY29rzvf//993jkkUcwc+ZMLF68mLt7toLX0nPxvVUOr6VyeC29kCumnTzNhx9+KKKiosSIESNEZGSkGDNmjFi1apUQwrLrZ+N88Z///GcxYcIE2+6fbBrYFK+l5+J7qxxeS+XwWnovrgLrgLq6OrzxxhtYunQpXnjhBfzyyy9Ys2YNunfvjn/961+orq6GRqOBJEm2fSLuueceVFVV4csvv0R5eTmEEDhy5AiAhhUF3ojX0nPxvVUOr6VyeC2JAVAHlJeX48yZM5g7dy5uvfVWGAwGjB49Gv369YPJZEJdXZ3tWI1GAyEE+vTpg9mzZ+OPP/7Ac889h+HDh+Omm26ydQf2VryWnovvrXJ4LZXDa0lMgdnpyJEjTaY9d+3aJerq6oQQDU3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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bp13['jet_width'].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c24b3da7-49cc-4512-9bbf-de56d128fc71",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Grise & Polvani 2014"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "05c3f613-c250-4c9d-92bb-7bea066595c3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 280 ms, sys: 14.6 ms, total: 295 ms\n",
      "Wall time: 283 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# This takes ~250 milliseconds on Intel i7-10750\n",
    "## For this example we look at only North Atlantic\n",
    "gp14 = jsmetrics.jet_statistics.grise_polvani_2014(\\\n",
    "                    ua.sel(lon=slice(300, 360), lat=slice(70, 20),\\\n",
    "                           plev=slice(700, 850)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "68fb1a55-2ebd-4b90-972e-2f3976c781ab",
   "metadata": {},
   "outputs": [
    {
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       "\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.Dataset&gt;\n",
       "Dimensions:    (lon: 60, lat: 51, plev: 2, time: 59)\n",
       "Coordinates:\n",
       "  * lon        (lon) float32 300.0 301.0 302.0 303.0 ... 356.0 357.0 358.0 359.0\n",
       "  * lat        (lat) float32 20.0 21.0 22.0 23.0 24.0 ... 67.0 68.0 69.0 70.0\n",
       "  * plev       (plev) int32 700 850\n",
       "  * time       (time) datetime64[ns] 2021-01-01 2021-01-02 ... 2021-02-28\n",
       "Data variables:\n",
       "    ua         (time, plev, lat, lon) float32 -6.866 -6.221 ... 20.13 21.39\n",
       "    jet_lat    (time) float64 45.42 54.74 26.44 34.18 ... 45.95 58.62 60.05\n",
       "    jet_speed  (time) float64 7.87 7.62 8.903 10.32 ... 12.73 15.81 13.03 16.61\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmw...</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-4f7d3e0a-fae9-4f1e-9175-44bb43c9c6f6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4f7d3e0a-fae9-4f1e-9175-44bb43c9c6f6' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 60</li><li><span class='xr-has-index'>lat</span>: 51</li><li><span class='xr-has-index'>plev</span>: 2</li><li><span class='xr-has-index'>time</span>: 59</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-52d75b56-1cb7-4555-9e49-20d26288d919' class='xr-section-summary-in' type='checkbox'  checked><label for='section-52d75b56-1cb7-4555-9e49-20d26288d919' 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'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>300.0 301.0 302.0 ... 358.0 359.0</div><input id='attrs-a478fe96-0b55-4d5e-9fbf-4dad84023df3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a478fe96-0b55-4d5e-9fbf-4dad84023df3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58dd449b-9209-46fa-a904-aa693bf6feb1' class='xr-var-data-in' type='checkbox'><label for='data-58dd449b-9209-46fa-a904-aa693bf6feb1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([300., 301., 302., 303., 304., 305., 306., 307., 308., 309., 310., 311.,\n",
       "       312., 313., 314., 315., 316., 317., 318., 319., 320., 321., 322., 323.,\n",
       "       324., 325., 326., 327., 328., 329., 330., 331., 332., 333., 334., 335.,\n",
       "       336., 337., 338., 339., 340., 341., 342., 343., 344., 345., 346., 347.,\n",
       "       348., 349., 350., 351., 352., 353., 354., 355., 356., 357., 358., 359.],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 21.0 22.0 ... 68.0 69.0 70.0</div><input id='attrs-b915f0b8-1729-45e6-95ed-983dea8794b9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b915f0b8-1729-45e6-95ed-983dea8794b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59ca4960-8f1c-440b-bb1c-eebd4e030665' class='xr-var-data-in' type='checkbox'><label for='data-59ca4960-8f1c-440b-bb1c-eebd4e030665' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([20., 21., 22., 23., 24., 25., 26., 27., 28., 29., 30., 31., 32., 33.,\n",
       "       34., 35., 36., 37., 38., 39., 40., 41., 42., 43., 44., 45., 46., 47.,\n",
       "       48., 49., 50., 51., 52., 53., 54., 55., 56., 57., 58., 59., 60., 61.,\n",
       "       62., 63., 64., 65., 66., 67., 68., 69., 70.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>plev</span></div><div class='xr-var-dims'>(plev)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>700 850</div><input id='attrs-e866f47b-a80e-4fc3-8eea-ae4315374420' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e866f47b-a80e-4fc3-8eea-ae4315374420' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a879b3a2-1b5c-4e83-a865-00b711161c1f' class='xr-var-data-in' type='checkbox'><label for='data-a879b3a2-1b5c-4e83-a865-00b711161c1f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>millibars</dd><dt><span>long_name :</span></dt><dd>pressure_level</dd></dl></div><div class='xr-var-data'><pre>array([700, 850], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-01-01 ... 2021-02-28</div><input id='attrs-59225a1e-9f34-4fdd-9ef1-929ed70b61b3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59225a1e-9f34-4fdd-9ef1-929ed70b61b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec00b9ea-3f5b-449e-a063-dd629369e7ff' class='xr-var-data-in' type='checkbox'><label for='data-ec00b9ea-3f5b-449e-a063-dd629369e7ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T00:00:00.000000000&#x27;, &#x27;2021-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-03T00:00:00.000000000&#x27;, &#x27;2021-01-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-05T00:00:00.000000000&#x27;, &#x27;2021-01-06T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-07T00:00:00.000000000&#x27;, &#x27;2021-01-08T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-09T00:00:00.000000000&#x27;, &#x27;2021-01-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-11T00:00:00.000000000&#x27;, &#x27;2021-01-12T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-13T00:00:00.000000000&#x27;, &#x27;2021-01-14T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-15T00:00:00.000000000&#x27;, &#x27;2021-01-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-17T00:00:00.000000000&#x27;, &#x27;2021-01-18T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-19T00:00:00.000000000&#x27;, &#x27;2021-01-20T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-21T00:00:00.000000000&#x27;, &#x27;2021-01-22T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-23T00:00:00.000000000&#x27;, &#x27;2021-01-24T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-25T00:00:00.000000000&#x27;, &#x27;2021-01-26T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-27T00:00:00.000000000&#x27;, &#x27;2021-01-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-29T00:00:00.000000000&#x27;, &#x27;2021-01-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-31T00:00:00.000000000&#x27;, &#x27;2021-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-02T00:00:00.000000000&#x27;, &#x27;2021-02-03T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-04T00:00:00.000000000&#x27;, &#x27;2021-02-05T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-06T00:00:00.000000000&#x27;, &#x27;2021-02-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-08T00:00:00.000000000&#x27;, &#x27;2021-02-09T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-10T00:00:00.000000000&#x27;, &#x27;2021-02-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-12T00:00:00.000000000&#x27;, &#x27;2021-02-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-14T00:00:00.000000000&#x27;, &#x27;2021-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-16T00:00:00.000000000&#x27;, &#x27;2021-02-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-18T00:00:00.000000000&#x27;, &#x27;2021-02-19T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-20T00:00:00.000000000&#x27;, &#x27;2021-02-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-22T00:00:00.000000000&#x27;, &#x27;2021-02-23T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-24T00:00:00.000000000&#x27;, &#x27;2021-02-25T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-26T00:00:00.000000000&#x27;, &#x27;2021-02-27T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-28T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3cd25b6a-0921-415f-ba67-d2d128e3f398' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3cd25b6a-0921-415f-ba67-d2d128e3f398' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ua</span></div><div class='xr-var-dims'>(time, plev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-6.866 -6.221 -5.24 ... 20.13 21.39</div><input id='attrs-0ad00e88-83e0-44c1-a0e7-e61aad7d7dd0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ad00e88-83e0-44c1-a0e7-e61aad7d7dd0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a504d5fa-b35e-4c7f-bc44-7107e1fe46ce' class='xr-var-data-in' type='checkbox'><label for='data-a504d5fa-b35e-4c7f-bc44-7107e1fe46ce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>U component of wind</dd><dt><span>standard_name :</span></dt><dd>eastward_wind</dd></dl></div><div class='xr-var-data'><pre>array([[[[ -6.865908, ...,  10.894857],\n",
       "         ...,\n",
       "         [ -0.338984, ...,  -0.290487]],\n",
       "\n",
       "        [[-10.779781, ...,   6.806973],\n",
       "         ...,\n",
       "         [  2.570747, ...,   4.208183]]],\n",
       "\n",
       "\n",
       "       ...,\n",
       "\n",
       "\n",
       "       [[[-10.440311, ...,   2.294037],\n",
       "         ...,\n",
       "         [ -3.208776, ...,  26.74433 ]],\n",
       "\n",
       "        [[-12.231792, ...,  -3.174543],\n",
       "         ...,\n",
       "         [ -0.133591, ...,  21.389854]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jet_lat</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>45.42 54.74 26.44 ... 58.62 60.05</div><input id='attrs-39bbf394-7d91-4fef-83a8-22f4fdf12e50' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-39bbf394-7d91-4fef-83a8-22f4fdf12e50' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a20ee37-a16f-4ac5-a93f-fadd132bf490' class='xr-var-data-in' type='checkbox'><label for='data-8a20ee37-a16f-4ac5-a93f-fadd132bf490' 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([45.42, 54.74, 26.44, 34.18, 32.54, 32.75, 29.58, 65.21, 61.44,\n",
       "       34.54, 55.06, 47.37, 53.39, 56.89, 50.68, 54.1 , 58.93, 41.49,\n",
       "       40.78, 36.08, 44.59, 40.99, 46.02, 38.71, 39.02, 39.57, 36.12,\n",
       "       45.26, 41.3 , 38.8 , 44.3 , 41.57, 44.42, 39.06, 43.19, 49.66,\n",
       "       46.38, 44.01, 44.58, 40.97, 39.41, 40.73, 41.88, 39.29, 41.83,\n",
       "       46.35, 45.21, 44.54, 44.2 , 41.63, 37.79, 37.49, 34.38, 43.85,\n",
       "       52.48, 43.49, 45.95, 58.62, 60.05])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jet_speed</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.87 7.62 8.903 ... 13.03 16.61</div><input id='attrs-ccbbbf76-1713-47f8-9675-993cdac51920' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ccbbbf76-1713-47f8-9675-993cdac51920' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-682b5057-8a4a-43c4-939d-28b4f7ee849b' class='xr-var-data-in' type='checkbox'><label for='data-682b5057-8a4a-43c4-939d-28b4f7ee849b' 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([ 7.87032279,  7.61959135,  8.90266736, 10.31645519, 14.64248222,\n",
       "       15.34045023, 14.57442947, 13.7252017 , 13.51106869,  9.2938774 ,\n",
       "       13.16876493, 14.27346711, 13.56828394, 12.21798764, 10.04287186,\n",
       "       12.72182477, 17.15104148, 12.66616602, 15.16173882, 20.2255164 ,\n",
       "       20.86766735, 22.33778033, 18.56424984, 17.56102545, 20.69703911,\n",
       "       17.00152724, 14.10942374, 15.06449486, 17.26746972, 24.07693764,\n",
       "       21.95139539, 19.74708658, 17.61501498, 14.60804851, 12.0147085 ,\n",
       "       10.81170875, 12.07104652, 18.76864548, 19.90624968, 26.42916085,\n",
       "       23.26498625, 20.91821988, 23.39663529, 20.69537987, 19.36356952,\n",
       "       14.92216859, 18.86110021, 19.83780293, 24.12173759, 20.28546296,\n",
       "       17.79995479, 18.09176778, 19.41492509, 16.501809  , 14.81347036,\n",
       "       12.73384161, 15.80871224, 13.02815055, 16.61365583])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e8c3794d-099b-4a12-b131-9bcb435dc268' class='xr-section-summary-in' type='checkbox'  ><label for='section-e8c3794d-099b-4a12-b131-9bcb435dc268' class='xr-section-summary' >Indexes: <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-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-825f9cce-9c4c-472f-9fab-f48c46e5d80c' class='xr-index-data-in' type='checkbox'/><label for='index-825f9cce-9c4c-472f-9fab-f48c46e5d80c' 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([300.0, 301.0, 302.0, 303.0, 304.0, 305.0, 306.0, 307.0, 308.0,\n",
       "              309.0, 310.0, 311.0, 312.0, 313.0, 314.0, 315.0, 316.0, 317.0,\n",
       "              318.0, 319.0, 320.0, 321.0, 322.0, 323.0, 324.0, 325.0, 326.0,\n",
       "              327.0, 328.0, 329.0, 330.0, 331.0, 332.0, 333.0, 334.0, 335.0,\n",
       "              336.0, 337.0, 338.0, 339.0, 340.0, 341.0, 342.0, 343.0, 344.0,\n",
       "              345.0, 346.0, 347.0, 348.0, 349.0, 350.0, 351.0, 352.0, 353.0,\n",
       "              354.0, 355.0, 356.0, 357.0, 358.0, 359.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;))</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-03b2686a-64b8-456c-a77c-934ef4d7f54f' class='xr-index-data-in' type='checkbox'/><label for='index-03b2686a-64b8-456c-a77c-934ef4d7f54f' 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([20.0, 21.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0,\n",
       "              31.0, 32.0, 33.0, 34.0, 35.0, 36.0, 37.0, 38.0, 39.0, 40.0, 41.0,\n",
       "              42.0, 43.0, 44.0, 45.0, 46.0, 47.0, 48.0, 49.0, 50.0, 51.0, 52.0,\n",
       "              53.0, 54.0, 55.0, 56.0, 57.0, 58.0, 59.0, 60.0, 61.0, 62.0, 63.0,\n",
       "              64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>plev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-88323345-efa8-4991-ba90-3dfdd1bd8300' class='xr-index-data-in' type='checkbox'/><label for='index-88323345-efa8-4991-ba90-3dfdd1bd8300' 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([700, 850], dtype=&#x27;int64&#x27;, name=&#x27;plev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-adbc6843-3b06-4cd5-9194-18f63042c1d1' class='xr-index-data-in' type='checkbox'/><label for='index-adbc6843-3b06-4cd5-9194-18f63042c1d1' 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;2021-01-01&#x27;, &#x27;2021-01-02&#x27;, &#x27;2021-01-03&#x27;, &#x27;2021-01-04&#x27;,\n",
       "               &#x27;2021-01-05&#x27;, &#x27;2021-01-06&#x27;, &#x27;2021-01-07&#x27;, &#x27;2021-01-08&#x27;,\n",
       "               &#x27;2021-01-09&#x27;, &#x27;2021-01-10&#x27;, &#x27;2021-01-11&#x27;, &#x27;2021-01-12&#x27;,\n",
       "               &#x27;2021-01-13&#x27;, &#x27;2021-01-14&#x27;, &#x27;2021-01-15&#x27;, &#x27;2021-01-16&#x27;,\n",
       "               &#x27;2021-01-17&#x27;, &#x27;2021-01-18&#x27;, &#x27;2021-01-19&#x27;, &#x27;2021-01-20&#x27;,\n",
       "               &#x27;2021-01-21&#x27;, &#x27;2021-01-22&#x27;, &#x27;2021-01-23&#x27;, &#x27;2021-01-24&#x27;,\n",
       "               &#x27;2021-01-25&#x27;, &#x27;2021-01-26&#x27;, &#x27;2021-01-27&#x27;, &#x27;2021-01-28&#x27;,\n",
       "               &#x27;2021-01-29&#x27;, &#x27;2021-01-30&#x27;, &#x27;2021-01-31&#x27;, &#x27;2021-02-01&#x27;,\n",
       "               &#x27;2021-02-02&#x27;, &#x27;2021-02-03&#x27;, &#x27;2021-02-04&#x27;, &#x27;2021-02-05&#x27;,\n",
       "               &#x27;2021-02-06&#x27;, &#x27;2021-02-07&#x27;, &#x27;2021-02-08&#x27;, &#x27;2021-02-09&#x27;,\n",
       "               &#x27;2021-02-10&#x27;, &#x27;2021-02-11&#x27;, &#x27;2021-02-12&#x27;, &#x27;2021-02-13&#x27;,\n",
       "               &#x27;2021-02-14&#x27;, &#x27;2021-02-15&#x27;, &#x27;2021-02-16&#x27;, &#x27;2021-02-17&#x27;,\n",
       "               &#x27;2021-02-18&#x27;, &#x27;2021-02-19&#x27;, &#x27;2021-02-20&#x27;, &#x27;2021-02-21&#x27;,\n",
       "               &#x27;2021-02-22&#x27;, &#x27;2021-02-23&#x27;, &#x27;2021-02-24&#x27;, &#x27;2021-02-25&#x27;,\n",
       "               &#x27;2021-02-26&#x27;, &#x27;2021-02-27&#x27;, &#x27;2021-02-28&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-633b6b2e-cc85-4012-8bf4-ca7647d71d30' class='xr-section-summary-in' type='checkbox'  checked><label for='section-633b6b2e-cc85-4012-8bf4-ca7647d71d30' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmwf/mars-client/bin/grib_to_netcdf -S param -o /cache/data6/adaptor.mars.internal-1645789868.3978655-14915-10-d5b8d9d1-2766-4630-b88f-1f6a21a2a0a4.nc /cache/tmp/d5b8d9d1-2766-4630-b88f-1f6a21a2a0a4-adaptor.mars.internal-1645789330.2418482-14915-17-tmp.grib</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (lon: 60, lat: 51, plev: 2, time: 59)\n",
       "Coordinates:\n",
       "  * lon        (lon) float32 300.0 301.0 302.0 303.0 ... 356.0 357.0 358.0 359.0\n",
       "  * lat        (lat) float32 20.0 21.0 22.0 23.0 24.0 ... 67.0 68.0 69.0 70.0\n",
       "  * plev       (plev) int32 700 850\n",
       "  * time       (time) datetime64[ns] 2021-01-01 2021-01-02 ... 2021-02-28\n",
       "Data variables:\n",
       "    ua         (time, plev, lat, lon) float32 -6.866 -6.221 ... 20.13 21.39\n",
       "    jet_lat    (time) float64 45.42 54.74 26.44 34.18 ... 45.95 58.62 60.05\n",
       "    jet_speed  (time) float64 7.87 7.62 8.903 10.32 ... 12.73 15.81 13.03 16.61\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmw..."
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gp14"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6a64a6e-6953-4494-b95a-ebfa35130dbc",
   "metadata": {},
   "source": [
    "### Barnes & Polvani 2015"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "94d32c15-349a-49b1-92b1-f4f1090e2967",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 185 ms, sys: 992 µs, total: 186 ms\n",
      "Wall time: 186 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# This takes ~250 milliseconds on Intel i7-10750\n",
    "## For this example we look at only North Atlantic\n",
    "bp15 = jsmetrics.jet_statistics.barnes_polvani_2015(\\\n",
    "                    ua.sel(lon=slice(300, 360), lat=slice(70, 20),\\\n",
    "                           plev=slice(700, 850)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "bac788ab-dfb4-4211-ad2a-20e5e9f7857e",
   "metadata": {},
   "outputs": [
    {
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       "  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.Dataset&gt;\n",
       "Dimensions:    (lat: 51, time: 59)\n",
       "Coordinates:\n",
       "  * lat        (lat) float32 20.0 21.0 22.0 23.0 24.0 ... 67.0 68.0 69.0 70.0\n",
       "  * time       (time) datetime64[ns] 2021-01-01 2021-01-02 ... 2021-02-28\n",
       "Data variables:\n",
       "    ua         (time, lat) float32 6.265 7.045 7.302 6.569 ... 8.566 6.973 6.54\n",
       "    jet_lat    (time) float64 46.68 34.18 48.62 51.24 ... 43.82 51.51 27.99\n",
       "    jet_speed  (time) float64 3.099 4.677 2.556 5.332 ... 9.967 7.867 1.401</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-77ff02ef-8469-4224-adc2-a347f2b4fa11' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-77ff02ef-8469-4224-adc2-a347f2b4fa11' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 51</li><li><span class='xr-has-index'>time</span>: 59</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9d898d36-5d8e-4d07-887c-ec27c2352ad7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9d898d36-5d8e-4d07-887c-ec27c2352ad7' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 21.0 22.0 ... 68.0 69.0 70.0</div><input id='attrs-12dcf5f4-6924-4c05-9b49-daf28f512922' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-12dcf5f4-6924-4c05-9b49-daf28f512922' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce834c21-031c-4080-bb69-fdb0e096129d' class='xr-var-data-in' type='checkbox'><label for='data-ce834c21-031c-4080-bb69-fdb0e096129d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([20., 21., 22., 23., 24., 25., 26., 27., 28., 29., 30., 31., 32., 33.,\n",
       "       34., 35., 36., 37., 38., 39., 40., 41., 42., 43., 44., 45., 46., 47.,\n",
       "       48., 49., 50., 51., 52., 53., 54., 55., 56., 57., 58., 59., 60., 61.,\n",
       "       62., 63., 64., 65., 66., 67., 68., 69., 70.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-01-01 ... 2021-02-28</div><input id='attrs-925f62d7-4d4d-45dd-a11a-4a0822b69571' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-925f62d7-4d4d-45dd-a11a-4a0822b69571' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a063d125-ea7e-414c-ab20-91956b471b55' class='xr-var-data-in' type='checkbox'><label for='data-a063d125-ea7e-414c-ab20-91956b471b55' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T00:00:00.000000000&#x27;, &#x27;2021-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-03T00:00:00.000000000&#x27;, &#x27;2021-01-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-05T00:00:00.000000000&#x27;, &#x27;2021-01-06T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-07T00:00:00.000000000&#x27;, &#x27;2021-01-08T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-09T00:00:00.000000000&#x27;, &#x27;2021-01-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-11T00:00:00.000000000&#x27;, &#x27;2021-01-12T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-13T00:00:00.000000000&#x27;, &#x27;2021-01-14T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-15T00:00:00.000000000&#x27;, &#x27;2021-01-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-17T00:00:00.000000000&#x27;, &#x27;2021-01-18T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-19T00:00:00.000000000&#x27;, &#x27;2021-01-20T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-21T00:00:00.000000000&#x27;, &#x27;2021-01-22T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-23T00:00:00.000000000&#x27;, &#x27;2021-01-24T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-25T00:00:00.000000000&#x27;, &#x27;2021-01-26T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-27T00:00:00.000000000&#x27;, &#x27;2021-01-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-29T00:00:00.000000000&#x27;, &#x27;2021-01-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-31T00:00:00.000000000&#x27;, &#x27;2021-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-02T00:00:00.000000000&#x27;, &#x27;2021-02-03T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-04T00:00:00.000000000&#x27;, &#x27;2021-02-05T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-06T00:00:00.000000000&#x27;, &#x27;2021-02-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-08T00:00:00.000000000&#x27;, &#x27;2021-02-09T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-10T00:00:00.000000000&#x27;, &#x27;2021-02-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-12T00:00:00.000000000&#x27;, &#x27;2021-02-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-14T00:00:00.000000000&#x27;, &#x27;2021-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-16T00:00:00.000000000&#x27;, &#x27;2021-02-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-18T00:00:00.000000000&#x27;, &#x27;2021-02-19T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-20T00:00:00.000000000&#x27;, &#x27;2021-02-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-22T00:00:00.000000000&#x27;, &#x27;2021-02-23T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-24T00:00:00.000000000&#x27;, &#x27;2021-02-25T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-26T00:00:00.000000000&#x27;, &#x27;2021-02-27T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-28T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f4044c54-7c7a-4511-a462-74feba0aa9e8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f4044c54-7c7a-4511-a462-74feba0aa9e8' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ua</span></div><div class='xr-var-dims'>(time, lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>6.265 7.045 7.302 ... 6.973 6.54</div><input id='attrs-b3628856-ebe6-4e52-b35e-cb024d2f2ca6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b3628856-ebe6-4e52-b35e-cb024d2f2ca6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6908320-f5f6-4202-a358-79bd426be5e6' class='xr-var-data-in' type='checkbox'><label for='data-e6908320-f5f6-4202-a358-79bd426be5e6' 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([[ 6.2652006 ,  7.0453367 ,  7.302196  , ...,  5.559306  ,\n",
       "         4.6819177 ,  4.043632  ],\n",
       "       [ 5.5461125 ,  5.8807316 ,  6.3271756 , ..., -0.13401814,\n",
       "         0.7061901 ,  1.538102  ],\n",
       "       [ 3.7577698 ,  4.7055955 ,  5.771403  , ...,  1.6448634 ,\n",
       "         2.3673513 ,  2.6989038 ],\n",
       "       ...,\n",
       "       [-8.831663  , -9.54671   , -9.428634  , ..., -3.8537421 ,\n",
       "        -2.0335917 , -1.1536362 ],\n",
       "       [-8.88149   , -8.137274  , -7.1395497 , ...,  0.7687113 ,\n",
       "        -0.9561358 , -2.920037  ],\n",
       "       [-4.2007704 , -3.6809652 , -2.86441   , ...,  8.565528  ,\n",
       "         6.972737  ,  6.5404606 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jet_lat</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.68 34.18 48.62 ... 51.51 27.99</div><input id='attrs-4d1d6f24-1e6c-4ebd-b011-575f69ffa9d0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4d1d6f24-1e6c-4ebd-b011-575f69ffa9d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89a0a8d6-0433-4624-8dc7-67518a38eab6' class='xr-var-data-in' type='checkbox'><label for='data-89a0a8d6-0433-4624-8dc7-67518a38eab6' 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([46.67903045, 34.17631773, 48.62423089, 51.24214139, 50.12566102,\n",
       "       59.80753814, 51.04392535, 41.7367812 , 30.33709061, 50.71827201,\n",
       "       44.31669143, 45.77692563, 51.49255091, 49.52364545, 45.93806999,\n",
       "       48.41949165,         nan, 44.12258759, 41.10227798, 42.84583977,\n",
       "       45.66569083, 42.46649047, 44.12158426, 43.93107475, 41.23152521,\n",
       "       43.29989706, 42.8372696 , 44.90115566, 44.90362251, 43.15316139,\n",
       "       42.69561431, 42.37836815, 42.81206965, 41.38369335, 42.44428421,\n",
       "       48.46918772, 50.14175474, 52.54300964, 48.19406613, 45.10254999,\n",
       "       44.76313093, 45.14034556, 45.40729732, 45.20234019, 44.86892189,\n",
       "       47.96447168, 44.57661191, 47.70453897, 45.15771567, 44.14784512,\n",
       "       44.40895174, 44.17833544, 41.13235578, 43.3154584 , 45.52706168,\n",
       "       43.47786616, 43.82136104, 51.5063272 , 27.98779533])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jet_speed</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.099 4.677 2.556 ... 7.867 1.401</div><input id='attrs-6e20ad56-8c3e-4239-8d9d-4fa4885f741c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6e20ad56-8c3e-4239-8d9d-4fa4885f741c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bedc99ae-87a7-4b5e-936d-7ed53c18907a' class='xr-var-data-in' type='checkbox'><label for='data-bedc99ae-87a7-4b5e-936d-7ed53c18907a' 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([ 3.09924896,  4.67728873,  2.55621021,  5.3319082 ,  6.21598094,\n",
       "        7.55089658,  5.09488822,  3.47871501,  4.11903677,  5.89903532,\n",
       "        7.58267565,  9.19769539,  9.78806851,  8.68764468,  7.0077599 ,\n",
       "        7.3763557 ,         nan,  8.02230985, 10.2979221 , 12.22735592,\n",
       "       13.73782286, 10.32461652, 11.52956708, 11.86451704, 11.3960628 ,\n",
       "       11.23582469,  9.52638545, 12.79013687, 12.56447291, 13.19175084,\n",
       "       13.89807335, 13.36029082, 12.18591377,  9.55142203,  7.46068525,\n",
       "        5.93606109,  8.00424731, 11.79238547, 13.4815824 , 17.38274672,\n",
       "       15.28446373, 14.19780926, 14.18553138, 12.70028318, 11.31193587,\n",
       "       11.29812313, 12.68687714, 12.76034725, 13.47635666, 13.75435402,\n",
       "       13.32643824, 13.25590265, 12.37221353, 12.4310619 , 11.2704323 ,\n",
       "       10.34010594,  9.96698451,  7.8666344 ,  1.40113388])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2ea1c35f-faa6-422a-ab8e-0598bb067f32' class='xr-section-summary-in' type='checkbox'  ><label for='section-2ea1c35f-faa6-422a-ab8e-0598bb067f32' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bc21a41c-4482-4ede-ad8b-33a1873c8ff6' class='xr-index-data-in' type='checkbox'/><label for='index-bc21a41c-4482-4ede-ad8b-33a1873c8ff6' 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([20.0, 21.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0,\n",
       "              31.0, 32.0, 33.0, 34.0, 35.0, 36.0, 37.0, 38.0, 39.0, 40.0, 41.0,\n",
       "              42.0, 43.0, 44.0, 45.0, 46.0, 47.0, 48.0, 49.0, 50.0, 51.0, 52.0,\n",
       "              53.0, 54.0, 55.0, 56.0, 57.0, 58.0, 59.0, 60.0, 61.0, 62.0, 63.0,\n",
       "              64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0a36676b-7465-48db-a0bf-99647ca8c728' class='xr-index-data-in' type='checkbox'/><label for='index-0a36676b-7465-48db-a0bf-99647ca8c728' 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;2021-01-01&#x27;, &#x27;2021-01-02&#x27;, &#x27;2021-01-03&#x27;, &#x27;2021-01-04&#x27;,\n",
       "               &#x27;2021-01-05&#x27;, &#x27;2021-01-06&#x27;, &#x27;2021-01-07&#x27;, &#x27;2021-01-08&#x27;,\n",
       "               &#x27;2021-01-09&#x27;, &#x27;2021-01-10&#x27;, &#x27;2021-01-11&#x27;, &#x27;2021-01-12&#x27;,\n",
       "               &#x27;2021-01-13&#x27;, &#x27;2021-01-14&#x27;, &#x27;2021-01-15&#x27;, &#x27;2021-01-16&#x27;,\n",
       "               &#x27;2021-01-17&#x27;, &#x27;2021-01-18&#x27;, &#x27;2021-01-19&#x27;, &#x27;2021-01-20&#x27;,\n",
       "               &#x27;2021-01-21&#x27;, &#x27;2021-01-22&#x27;, &#x27;2021-01-23&#x27;, &#x27;2021-01-24&#x27;,\n",
       "               &#x27;2021-01-25&#x27;, &#x27;2021-01-26&#x27;, &#x27;2021-01-27&#x27;, &#x27;2021-01-28&#x27;,\n",
       "               &#x27;2021-01-29&#x27;, &#x27;2021-01-30&#x27;, &#x27;2021-01-31&#x27;, &#x27;2021-02-01&#x27;,\n",
       "               &#x27;2021-02-02&#x27;, &#x27;2021-02-03&#x27;, &#x27;2021-02-04&#x27;, &#x27;2021-02-05&#x27;,\n",
       "               &#x27;2021-02-06&#x27;, &#x27;2021-02-07&#x27;, &#x27;2021-02-08&#x27;, &#x27;2021-02-09&#x27;,\n",
       "               &#x27;2021-02-10&#x27;, &#x27;2021-02-11&#x27;, &#x27;2021-02-12&#x27;, &#x27;2021-02-13&#x27;,\n",
       "               &#x27;2021-02-14&#x27;, &#x27;2021-02-15&#x27;, &#x27;2021-02-16&#x27;, &#x27;2021-02-17&#x27;,\n",
       "               &#x27;2021-02-18&#x27;, &#x27;2021-02-19&#x27;, &#x27;2021-02-20&#x27;, &#x27;2021-02-21&#x27;,\n",
       "               &#x27;2021-02-22&#x27;, &#x27;2021-02-23&#x27;, &#x27;2021-02-24&#x27;, &#x27;2021-02-25&#x27;,\n",
       "               &#x27;2021-02-26&#x27;, &#x27;2021-02-27&#x27;, &#x27;2021-02-28&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9c52063f-f402-43ae-8a14-c0cde53977f9' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9c52063f-f402-43ae-8a14-c0cde53977f9' 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.Dataset>\n",
       "Dimensions:    (lat: 51, time: 59)\n",
       "Coordinates:\n",
       "  * lat        (lat) float32 20.0 21.0 22.0 23.0 24.0 ... 67.0 68.0 69.0 70.0\n",
       "  * time       (time) datetime64[ns] 2021-01-01 2021-01-02 ... 2021-02-28\n",
       "Data variables:\n",
       "    ua         (time, lat) float32 6.265 7.045 7.302 6.569 ... 8.566 6.973 6.54\n",
       "    jet_lat    (time) float64 46.68 34.18 48.62 51.24 ... 43.82 51.51 27.99\n",
       "    jet_speed  (time) float64 3.099 4.677 2.556 5.332 ... 9.967 7.867 1.401"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bp15"
   ]
  },
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   "cell_type": "markdown",
   "id": "46c4fb70-594e-4155-9c3d-1f44a3c24e1a",
   "metadata": {},
   "source": [
    "### Barnes & Simpson 2017"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4638ed78-7a9e-47e1-b0a0-2c4251985687",
   "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this metric was meant to only work on one plev, please subset plev to one value. For now taking the mean...\n",
      "CPU times: user 15.6 ms, sys: 3.83 ms, total: 19.5 ms\n",
      "Wall time: 19 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# This takes ~30 milliseconds on Intel i7-10750\n",
    "## For this example we look at only North Atlantic\n",
    "bs17 = jsmetrics.jet_statistics.barnes_simpson_2017(\\\n",
    "                    ua.sel(lon=slice(300, 360), lat=slice(70, 20),\\\n",
    "                           plev=slice(700, 850)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5e468152-87d7-4950-b77b-337009d5786d",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (lat: 51, time: 6)\n",
       "Coordinates:\n",
       "  * lat        (lat) float32 20.0 21.0 22.0 23.0 24.0 ... 67.0 68.0 69.0 70.0\n",
       "  * time       (time) datetime64[ns] 2021-01-01 2021-01-11 ... 2021-02-20\n",
       "Data variables:\n",
       "    ua         (time, lat) float32 3.603 4.651 5.781 ... -1.923 -1.835 -2.256\n",
       "    jet_lat    (time) float32 27.0 38.0 40.0 44.0 42.0 39.0\n",
       "    jet_speed  (time) float32 8.334 9.902 17.19 15.99 19.27 11.71</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-ef7486e1-6b3e-4c31-b665-56087c8d5a3c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ef7486e1-6b3e-4c31-b665-56087c8d5a3c' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 51</li><li><span class='xr-has-index'>time</span>: 6</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-89d751e8-feb6-42c7-b1cb-54786f2f4b22' class='xr-section-summary-in' type='checkbox'  checked><label for='section-89d751e8-feb6-42c7-b1cb-54786f2f4b22' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 21.0 22.0 ... 68.0 69.0 70.0</div><input id='attrs-fb68bfbf-7e35-4b91-ac91-e1c4e908d0a8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fb68bfbf-7e35-4b91-ac91-e1c4e908d0a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c878aadc-a8bb-4045-9363-1bbec4e9d25d' class='xr-var-data-in' type='checkbox'><label for='data-c878aadc-a8bb-4045-9363-1bbec4e9d25d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([20., 21., 22., 23., 24., 25., 26., 27., 28., 29., 30., 31., 32., 33.,\n",
       "       34., 35., 36., 37., 38., 39., 40., 41., 42., 43., 44., 45., 46., 47.,\n",
       "       48., 49., 50., 51., 52., 53., 54., 55., 56., 57., 58., 59., 60., 61.,\n",
       "       62., 63., 64., 65., 66., 67., 68., 69., 70.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-01-01 ... 2021-02-20</div><input id='attrs-c01d57f5-c91f-4c58-b565-83ac0bb7238f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c01d57f5-c91f-4c58-b565-83ac0bb7238f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e026f1cb-a575-40d2-95da-94002975bc6c' class='xr-var-data-in' type='checkbox'><label for='data-e026f1cb-a575-40d2-95da-94002975bc6c' 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;2021-01-01T00:00:00.000000000&#x27;, &#x27;2021-01-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-21T00:00:00.000000000&#x27;, &#x27;2021-01-31T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-10T00:00:00.000000000&#x27;, &#x27;2021-02-20T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e1fc8240-0d6f-476d-8d72-5ed11498349e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e1fc8240-0d6f-476d-8d72-5ed11498349e' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ua</span></div><div class='xr-var-dims'>(time, lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.603 4.651 5.781 ... -1.835 -2.256</div><input id='attrs-93eadd8d-21de-4c40-a0d4-ae9888a66b74' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-93eadd8d-21de-4c40-a0d4-ae9888a66b74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43b1a464-a2cb-42a5-ac9a-858d4fb9d05d' class='xr-var-data-in' type='checkbox'><label for='data-43b1a464-a2cb-42a5-ac9a-858d4fb9d05d' 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([[ 3.6025054 ,  4.6505175 ,  5.7810144 ,  6.533676  ,  7.120778  ,\n",
       "         7.658441  ,  8.131029  ,  8.3343935 ,  8.303841  ,  8.252501  ,\n",
       "         8.267763  ,  7.993445  ,  7.898919  ,  7.9110413 ,  7.260453  ,\n",
       "         6.2188687 ,  5.184115  ,  3.789641  ,  2.4943857 ,  1.1190889 ,\n",
       "         0.03365264, -0.5590764 , -0.9213425 , -1.3576812 , -1.7193264 ,\n",
       "        -1.9975815 , -1.9603729 , -1.6284357 , -1.4353284 , -1.167638  ,\n",
       "        -0.82916087, -0.5679385 , -0.224612  ,  0.35645437,  1.3536787 ,\n",
       "         2.573417  ,  3.6030974 ,  4.5178013 ,  5.374408  ,  6.0905867 ,\n",
       "         6.6478424 ,  7.0486336 ,  7.475464  ,  7.6677866 ,  7.8742895 ,\n",
       "         7.7315383 ,  6.948058  ,  6.4625382 ,  5.5132856 ,  4.1540804 ,\n",
       "         3.4271183 ],\n",
       "       [-4.305269  , -4.2916565 , -4.069354  , -3.626379  , -3.041376  ,\n",
       "        -2.3404875 , -1.5570903 , -0.57211804,  0.6181139 ,  1.861296  ,\n",
       "         3.0878282 ,  4.394742  ,  5.701353  ,  6.8569007 ,  7.9354486 ,\n",
       "         8.904909  ,  9.450388  ,  9.787462  ,  9.901798  ,  9.712046  ,\n",
       "         9.665556  ,  9.6443205 ,  9.446951  ,  9.116142  ,  8.907674  ,\n",
       "         8.704112  ,  8.465292  ,  8.040874  ,  7.371184  ,  6.797354  ,\n",
       "         6.3800573 ,  6.3709707 ,  6.4147787 ,  6.6005173 ,  6.5877085 ,\n",
       "         6.8384132 ,  6.7582793 ,  6.1284513 ,  5.571199  ,  4.502059  ,\n",
       "         3.047479  ,  1.5493056 , -0.08643766, -1.4556205 , -2.2988029 ,\n",
       "...\n",
       "         3.0954401 ,  4.704568  ,  6.3882756 ,  8.133557  ,  9.8871975 ,\n",
       "        11.5026655 , 13.269814  , 14.796277  , 16.13702   , 17.341862  ,\n",
       "        18.133772  , 18.805187  , 19.269978  , 19.002613  , 18.488932  ,\n",
       "        17.55737   , 16.336557  , 14.724141  , 12.524392  , 10.2008705 ,\n",
       "         8.10832   ,  6.2024736 ,  4.7251983 ,  3.3542824 ,  1.7559944 ,\n",
       "         0.430341  , -0.6774013 , -1.4938755 , -1.6499212 , -1.4175375 ,\n",
       "        -1.2692264 , -1.7087383 , -2.270804  , -3.3667285 , -4.161154  ,\n",
       "        -4.1775713 , -4.4382105 , -4.378922  , -4.4269066 , -3.6623275 ,\n",
       "        -3.1331058 ],\n",
       "       [-5.579194  , -5.133326  , -4.282402  , -3.379855  , -2.3533423 ,\n",
       "        -0.99142194,  0.36532953,  1.6835754 ,  2.9331481 ,  4.204317  ,\n",
       "         5.3108783 ,  6.5299697 ,  7.889183  ,  9.113747  ,  9.9281435 ,\n",
       "        10.563847  , 10.886643  , 11.193012  , 11.509485  , 11.706669  ,\n",
       "        11.618875  , 11.560792  , 11.439091  , 11.317959  , 10.998061  ,\n",
       "        10.667192  , 10.366884  ,  9.9075575 ,  9.494328  ,  9.142969  ,\n",
       "         8.771243  ,  9.073139  ,  9.499304  ,  9.712056  ,  9.521492  ,\n",
       "         9.045497  ,  8.407162  ,  7.8356814 ,  7.490667  ,  7.0205526 ,\n",
       "         6.115015  ,  4.523008  ,  2.9719315 ,  1.7754579 ,  0.2777708 ,\n",
       "        -0.82901466, -1.6388874 , -1.9547418 , -1.9231483 , -1.8353282 ,\n",
       "        -2.2555752 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jet_lat</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>27.0 38.0 40.0 44.0 42.0 39.0</div><input id='attrs-a9616850-093d-4844-80bf-9d037d0e2c1b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a9616850-093d-4844-80bf-9d037d0e2c1b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe83b5d5-446d-4263-935a-7e3c14467081' class='xr-var-data-in' type='checkbox'><label for='data-fe83b5d5-446d-4263-935a-7e3c14467081' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([27., 38., 40., 44., 42., 39.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jet_speed</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>8.334 9.902 17.19 15.99 19.27 11.71</div><input id='attrs-a666aac3-e069-4ba5-8c6e-7efbfd4ee9e5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a666aac3-e069-4ba5-8c6e-7efbfd4ee9e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c77c9cd6-7901-4673-8bae-6e824c400123' class='xr-var-data-in' type='checkbox'><label for='data-c77c9cd6-7901-4673-8bae-6e824c400123' 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([ 8.3343935,  9.901798 , 17.194029 , 15.991877 , 19.269978 ,\n",
       "       11.706669 ], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-87cbd9b3-4b40-413c-988d-bcf7a3defcde' class='xr-section-summary-in' type='checkbox'  ><label for='section-87cbd9b3-4b40-413c-988d-bcf7a3defcde' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4f473031-93c1-4fbd-8a76-a87677870b58' class='xr-index-data-in' type='checkbox'/><label for='index-4f473031-93c1-4fbd-8a76-a87677870b58' 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([20.0, 21.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0,\n",
       "              31.0, 32.0, 33.0, 34.0, 35.0, 36.0, 37.0, 38.0, 39.0, 40.0, 41.0,\n",
       "              42.0, 43.0, 44.0, 45.0, 46.0, 47.0, 48.0, 49.0, 50.0, 51.0, 52.0,\n",
       "              53.0, 54.0, 55.0, 56.0, 57.0, 58.0, 59.0, 60.0, 61.0, 62.0, 63.0,\n",
       "              64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-518ee37f-f3cc-40cf-a34d-7ec08bf4dcf0' class='xr-index-data-in' type='checkbox'/><label for='index-518ee37f-f3cc-40cf-a34d-7ec08bf4dcf0' 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;2021-01-01&#x27;, &#x27;2021-01-11&#x27;, &#x27;2021-01-21&#x27;, &#x27;2021-01-31&#x27;,\n",
       "               &#x27;2021-02-10&#x27;, &#x27;2021-02-20&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=&#x27;10D&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f366cf00-309a-4be0-a7b4-0061263b7184' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f366cf00-309a-4be0-a7b4-0061263b7184' 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.Dataset>\n",
       "Dimensions:    (lat: 51, time: 6)\n",
       "Coordinates:\n",
       "  * lat        (lat) float32 20.0 21.0 22.0 23.0 24.0 ... 67.0 68.0 69.0 70.0\n",
       "  * time       (time) datetime64[ns] 2021-01-01 2021-01-11 ... 2021-02-20\n",
       "Data variables:\n",
       "    ua         (time, lat) float32 3.603 4.651 5.781 ... -1.923 -1.835 -2.256\n",
       "    jet_lat    (time) float32 27.0 38.0 40.0 44.0 42.0 39.0\n",
       "    jet_speed  (time) float32 8.334 9.902 17.19 15.99 19.27 11.71"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bs17"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84cf845e-a740-42a2-94d6-2b70d5421f93",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Bracegirdle et al. 2018"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "0fb37b37-0926-477d-a5d5-1c24a4126d11",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 88.5 ms, sys: 0 ns, total: 88.5 ms\n",
      "Wall time: 88 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# This takes ~150 milliseconds on Intel i7-10750\n",
    "## For this example we look at only North Atlantic\n",
    "b18 = jsmetrics.jet_statistics.bracegirdle_et_al_2018(\\\n",
    "                    ua.sel(lon=slice(300, 360), lat=slice(70, 20),\\\n",
    "                           plev=slice(850, 850)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "dac33fae-f2ae-42c7-886d-2835cbed6132",
   "metadata": {},
   "outputs": [
    {
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       "  --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.Dataset&gt;\n",
       "Dimensions:        (lon: 60, lat: 51, time: 59, season: 1, year: 1)\n",
       "Coordinates:\n",
       "  * lon            (lon) float32 300.0 301.0 302.0 303.0 ... 357.0 358.0 359.0\n",
       "  * lat            (lat) float32 20.0 21.0 22.0 23.0 ... 67.0 68.0 69.0 70.0\n",
       "    plev           int32 850\n",
       "  * time           (time) datetime64[ns] 2021-01-01 2021-01-02 ... 2021-02-28\n",
       "Dimensions without coordinates: season, year\n",
       "Data variables:\n",
       "    ua             (time, lat, lon) float32 ...\n",
       "    seasonal_JPOS  (season) float64 41.52\n",
       "    annual_JPOS    (year) float64 41.52\n",
       "    seasonal_JSTR  (season) float64 9.782\n",
       "    annual_JSTR    (year) float64 9.782\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmw...</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-553f251e-32b9-4070-bd3e-168953be3ef6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-553f251e-32b9-4070-bd3e-168953be3ef6' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 60</li><li><span class='xr-has-index'>lat</span>: 51</li><li><span class='xr-has-index'>time</span>: 59</li><li><span>season</span>: 1</li><li><span>year</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-4482b126-ff3a-4bdc-a98f-147acfa6342a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4482b126-ff3a-4bdc-a98f-147acfa6342a' 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'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>300.0 301.0 302.0 ... 358.0 359.0</div><input id='attrs-c785acbc-13dc-424f-b041-fa4b1fd78ba9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c785acbc-13dc-424f-b041-fa4b1fd78ba9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-810d088f-3cec-4ea6-a920-99fe82d523a8' class='xr-var-data-in' type='checkbox'><label for='data-810d088f-3cec-4ea6-a920-99fe82d523a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([300., 301., 302., 303., 304., 305., 306., 307., 308., 309., 310., 311.,\n",
       "       312., 313., 314., 315., 316., 317., 318., 319., 320., 321., 322., 323.,\n",
       "       324., 325., 326., 327., 328., 329., 330., 331., 332., 333., 334., 335.,\n",
       "       336., 337., 338., 339., 340., 341., 342., 343., 344., 345., 346., 347.,\n",
       "       348., 349., 350., 351., 352., 353., 354., 355., 356., 357., 358., 359.],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 21.0 22.0 ... 68.0 69.0 70.0</div><input id='attrs-d450be7b-1611-4299-93e0-de9b9177c375' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d450be7b-1611-4299-93e0-de9b9177c375' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3295e8fd-6aaa-4f49-b240-a5ae49ee6578' class='xr-var-data-in' type='checkbox'><label for='data-3295e8fd-6aaa-4f49-b240-a5ae49ee6578' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([20., 21., 22., 23., 24., 25., 26., 27., 28., 29., 30., 31., 32., 33.,\n",
       "       34., 35., 36., 37., 38., 39., 40., 41., 42., 43., 44., 45., 46., 47.,\n",
       "       48., 49., 50., 51., 52., 53., 54., 55., 56., 57., 58., 59., 60., 61.,\n",
       "       62., 63., 64., 65., 66., 67., 68., 69., 70.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>plev</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>850</div><input id='attrs-f71afa21-798c-45fc-8f50-172e8202427a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f71afa21-798c-45fc-8f50-172e8202427a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-09ae0219-5dbc-4f51-920c-7216889fd076' class='xr-var-data-in' type='checkbox'><label for='data-09ae0219-5dbc-4f51-920c-7216889fd076' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>millibars</dd><dt><span>long_name :</span></dt><dd>pressure_level</dd></dl></div><div class='xr-var-data'><pre>array(850, dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-01-01 ... 2021-02-28</div><input id='attrs-88647d5f-3cae-4f35-8803-d4e6cd463464' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88647d5f-3cae-4f35-8803-d4e6cd463464' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23930935-c47f-46a8-9906-0a8b283f2238' class='xr-var-data-in' type='checkbox'><label for='data-23930935-c47f-46a8-9906-0a8b283f2238' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T00:00:00.000000000&#x27;, &#x27;2021-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-03T00:00:00.000000000&#x27;, &#x27;2021-01-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-05T00:00:00.000000000&#x27;, &#x27;2021-01-06T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-07T00:00:00.000000000&#x27;, &#x27;2021-01-08T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-09T00:00:00.000000000&#x27;, &#x27;2021-01-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-11T00:00:00.000000000&#x27;, &#x27;2021-01-12T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-13T00:00:00.000000000&#x27;, &#x27;2021-01-14T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-15T00:00:00.000000000&#x27;, &#x27;2021-01-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-17T00:00:00.000000000&#x27;, &#x27;2021-01-18T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-19T00:00:00.000000000&#x27;, &#x27;2021-01-20T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-21T00:00:00.000000000&#x27;, &#x27;2021-01-22T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-23T00:00:00.000000000&#x27;, &#x27;2021-01-24T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-25T00:00:00.000000000&#x27;, &#x27;2021-01-26T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-27T00:00:00.000000000&#x27;, &#x27;2021-01-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-29T00:00:00.000000000&#x27;, &#x27;2021-01-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-31T00:00:00.000000000&#x27;, &#x27;2021-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-02T00:00:00.000000000&#x27;, &#x27;2021-02-03T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-04T00:00:00.000000000&#x27;, &#x27;2021-02-05T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-06T00:00:00.000000000&#x27;, &#x27;2021-02-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-08T00:00:00.000000000&#x27;, &#x27;2021-02-09T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-10T00:00:00.000000000&#x27;, &#x27;2021-02-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-12T00:00:00.000000000&#x27;, &#x27;2021-02-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-14T00:00:00.000000000&#x27;, &#x27;2021-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-16T00:00:00.000000000&#x27;, &#x27;2021-02-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-18T00:00:00.000000000&#x27;, &#x27;2021-02-19T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-20T00:00:00.000000000&#x27;, &#x27;2021-02-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-22T00:00:00.000000000&#x27;, &#x27;2021-02-23T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-24T00:00:00.000000000&#x27;, &#x27;2021-02-25T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-26T00:00:00.000000000&#x27;, &#x27;2021-02-27T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-28T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-03b58a8e-2f3f-4461-a441-6bb4a071e21f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-03b58a8e-2f3f-4461-a441-6bb4a071e21f' class='xr-section-summary' >Data variables: <span>(5)</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>ua</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7f83b273-3c91-4dac-8fb6-4e41c933250a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f83b273-3c91-4dac-8fb6-4e41c933250a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72179089-58ad-4153-a066-44907aa63ac9' class='xr-var-data-in' type='checkbox'><label for='data-72179089-58ad-4153-a066-44907aa63ac9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>U component of wind</dd><dt><span>standard_name :</span></dt><dd>eastward_wind</dd></dl></div><div class='xr-var-data'><pre>[180540 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>seasonal_JPOS</span></div><div class='xr-var-dims'>(season)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>41.52</div><input id='attrs-061dae8b-185e-4d03-b427-f9df35af3751' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-061dae8b-185e-4d03-b427-f9df35af3751' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3720afa-cc6d-4b14-9791-f1f3e6036e68' class='xr-var-data-in' type='checkbox'><label for='data-a3720afa-cc6d-4b14-9791-f1f3e6036e68' 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([41.525])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>annual_JPOS</span></div><div class='xr-var-dims'>(year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>41.52</div><input id='attrs-27557bc1-cb90-44dc-9ec5-7f4f95c2fbee' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-27557bc1-cb90-44dc-9ec5-7f4f95c2fbee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-023bbd42-d315-4730-8e6c-deb1ea141d1a' class='xr-var-data-in' type='checkbox'><label for='data-023bbd42-d315-4730-8e6c-deb1ea141d1a' 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([41.525])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>seasonal_JSTR</span></div><div class='xr-var-dims'>(season)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.782</div><input id='attrs-33e04711-8448-46e0-a6d3-0a9835f505b5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-33e04711-8448-46e0-a6d3-0a9835f505b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a76a435e-3330-4dfe-afa0-4145059cc022' class='xr-var-data-in' type='checkbox'><label for='data-a76a435e-3330-4dfe-afa0-4145059cc022' 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([9.78150288])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>annual_JSTR</span></div><div class='xr-var-dims'>(year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.782</div><input id='attrs-10442510-91e8-4818-8259-2c322dc2d4fd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-10442510-91e8-4818-8259-2c322dc2d4fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a2cff09-f4f3-41f1-a3ee-207909079239' class='xr-var-data-in' type='checkbox'><label for='data-2a2cff09-f4f3-41f1-a3ee-207909079239' 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([9.78150288])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b8413913-a831-4a29-bfa7-531b88db061b' class='xr-section-summary-in' type='checkbox'  ><label for='section-b8413913-a831-4a29-bfa7-531b88db061b' 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-02cf4c7c-fbad-4154-b34f-a8626286a1c9' class='xr-index-data-in' type='checkbox'/><label for='index-02cf4c7c-fbad-4154-b34f-a8626286a1c9' 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([300.0, 301.0, 302.0, 303.0, 304.0, 305.0, 306.0, 307.0, 308.0,\n",
       "              309.0, 310.0, 311.0, 312.0, 313.0, 314.0, 315.0, 316.0, 317.0,\n",
       "              318.0, 319.0, 320.0, 321.0, 322.0, 323.0, 324.0, 325.0, 326.0,\n",
       "              327.0, 328.0, 329.0, 330.0, 331.0, 332.0, 333.0, 334.0, 335.0,\n",
       "              336.0, 337.0, 338.0, 339.0, 340.0, 341.0, 342.0, 343.0, 344.0,\n",
       "              345.0, 346.0, 347.0, 348.0, 349.0, 350.0, 351.0, 352.0, 353.0,\n",
       "              354.0, 355.0, 356.0, 357.0, 358.0, 359.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;))</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-65055486-72a8-4f0f-a40e-12679f982e48' class='xr-index-data-in' type='checkbox'/><label for='index-65055486-72a8-4f0f-a40e-12679f982e48' 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([20.0, 21.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0,\n",
       "              31.0, 32.0, 33.0, 34.0, 35.0, 36.0, 37.0, 38.0, 39.0, 40.0, 41.0,\n",
       "              42.0, 43.0, 44.0, 45.0, 46.0, 47.0, 48.0, 49.0, 50.0, 51.0, 52.0,\n",
       "              53.0, 54.0, 55.0, 56.0, 57.0, 58.0, 59.0, 60.0, 61.0, 62.0, 63.0,\n",
       "              64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1210a2a2-98a9-4539-94c4-2ebbf08f5bd0' class='xr-index-data-in' type='checkbox'/><label for='index-1210a2a2-98a9-4539-94c4-2ebbf08f5bd0' 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;2021-01-01&#x27;, &#x27;2021-01-02&#x27;, &#x27;2021-01-03&#x27;, &#x27;2021-01-04&#x27;,\n",
       "               &#x27;2021-01-05&#x27;, &#x27;2021-01-06&#x27;, &#x27;2021-01-07&#x27;, &#x27;2021-01-08&#x27;,\n",
       "               &#x27;2021-01-09&#x27;, &#x27;2021-01-10&#x27;, &#x27;2021-01-11&#x27;, &#x27;2021-01-12&#x27;,\n",
       "               &#x27;2021-01-13&#x27;, &#x27;2021-01-14&#x27;, &#x27;2021-01-15&#x27;, &#x27;2021-01-16&#x27;,\n",
       "               &#x27;2021-01-17&#x27;, &#x27;2021-01-18&#x27;, &#x27;2021-01-19&#x27;, &#x27;2021-01-20&#x27;,\n",
       "               &#x27;2021-01-21&#x27;, &#x27;2021-01-22&#x27;, &#x27;2021-01-23&#x27;, &#x27;2021-01-24&#x27;,\n",
       "               &#x27;2021-01-25&#x27;, &#x27;2021-01-26&#x27;, &#x27;2021-01-27&#x27;, &#x27;2021-01-28&#x27;,\n",
       "               &#x27;2021-01-29&#x27;, &#x27;2021-01-30&#x27;, &#x27;2021-01-31&#x27;, &#x27;2021-02-01&#x27;,\n",
       "               &#x27;2021-02-02&#x27;, &#x27;2021-02-03&#x27;, &#x27;2021-02-04&#x27;, &#x27;2021-02-05&#x27;,\n",
       "               &#x27;2021-02-06&#x27;, &#x27;2021-02-07&#x27;, &#x27;2021-02-08&#x27;, &#x27;2021-02-09&#x27;,\n",
       "               &#x27;2021-02-10&#x27;, &#x27;2021-02-11&#x27;, &#x27;2021-02-12&#x27;, &#x27;2021-02-13&#x27;,\n",
       "               &#x27;2021-02-14&#x27;, &#x27;2021-02-15&#x27;, &#x27;2021-02-16&#x27;, &#x27;2021-02-17&#x27;,\n",
       "               &#x27;2021-02-18&#x27;, &#x27;2021-02-19&#x27;, &#x27;2021-02-20&#x27;, &#x27;2021-02-21&#x27;,\n",
       "               &#x27;2021-02-22&#x27;, &#x27;2021-02-23&#x27;, &#x27;2021-02-24&#x27;, &#x27;2021-02-25&#x27;,\n",
       "               &#x27;2021-02-26&#x27;, &#x27;2021-02-27&#x27;, &#x27;2021-02-28&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2048faf2-83ef-48c6-80e4-007cf55b0d0a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2048faf2-83ef-48c6-80e4-007cf55b0d0a' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmwf/mars-client/bin/grib_to_netcdf -S param -o /cache/data6/adaptor.mars.internal-1645789868.3978655-14915-10-d5b8d9d1-2766-4630-b88f-1f6a21a2a0a4.nc /cache/tmp/d5b8d9d1-2766-4630-b88f-1f6a21a2a0a4-adaptor.mars.internal-1645789330.2418482-14915-17-tmp.grib</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:        (lon: 60, lat: 51, time: 59, season: 1, year: 1)\n",
       "Coordinates:\n",
       "  * lon            (lon) float32 300.0 301.0 302.0 303.0 ... 357.0 358.0 359.0\n",
       "  * lat            (lat) float32 20.0 21.0 22.0 23.0 ... 67.0 68.0 69.0 70.0\n",
       "    plev           int32 850\n",
       "  * time           (time) datetime64[ns] 2021-01-01 2021-01-02 ... 2021-02-28\n",
       "Dimensions without coordinates: season, year\n",
       "Data variables:\n",
       "    ua             (time, lat, lon) float32 ...\n",
       "    seasonal_JPOS  (season) float64 41.52\n",
       "    annual_JPOS    (year) float64 41.52\n",
       "    seasonal_JSTR  (season) float64 9.782\n",
       "    annual_JSTR    (year) float64 9.782\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmw..."
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b18"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66e70b65-edf5-4ff6-b729-7f2bf5b04f06",
   "metadata": {},
   "source": [
    "### Ceppi et al. 2018"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "867dce3e-1f97-4dc4-8ac1-be33c9dd9084",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 47.4 ms, sys: 10.8 ms, total: 58.2 ms\n",
      "Wall time: 57.2 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# This takes ~100 milliseconds on Intel i7-10750\n",
    "## For this example we look at only North Atlantic\n",
    "c18 = jsmetrics.jet_statistics.ceppi_et_al_2018(\\\n",
    "                    ua.sel(lon=slice(300, 360), lat=slice(70, 20),\\\n",
    "                           plev=slice(850, 850)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b3a778cd-619a-4c48-aadd-a3a0f9ba2c66",
   "metadata": {},
   "outputs": [
    {
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       "  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.Dataset&gt;\n",
       "Dimensions:        (lon: 60, lat: 51, plev: 1, time: 59)\n",
       "Coordinates:\n",
       "  * lon            (lon) float32 300.0 301.0 302.0 303.0 ... 357.0 358.0 359.0\n",
       "  * lat            (lat) float32 20.0 21.0 22.0 23.0 ... 67.0 68.0 69.0 70.0\n",
       "  * plev           (plev) int32 850\n",
       "  * time           (time) datetime64[ns] 2021-01-01 2021-01-02 ... 2021-02-28\n",
       "Data variables:\n",
       "    ua             (time, plev, lat, lon) float32 -10.78 -9.664 ... 20.13 21.39\n",
       "    total_area_m2  (lat, lon) float64 1.162e+10 1.162e+10 ... 4.229e+09\n",
       "    jet_lat        (time, plev) float64 46.2 46.16 42.01 ... 41.3 45.94 56.45\n",
       "    jet_speed      (time) float64 6.109 3.312 -1.714 ... 9.023 6.115 9.825\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmw...</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-303a35e9-ead7-40c4-af13-ef4e9e6a8487' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-303a35e9-ead7-40c4-af13-ef4e9e6a8487' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 60</li><li><span class='xr-has-index'>lat</span>: 51</li><li><span class='xr-has-index'>plev</span>: 1</li><li><span class='xr-has-index'>time</span>: 59</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ed7cd8c8-ef71-4f1b-a0f0-d67448450730' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ed7cd8c8-ef71-4f1b-a0f0-d67448450730' 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'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>300.0 301.0 302.0 ... 358.0 359.0</div><input id='attrs-7b024e6d-14f8-4c2f-8ee7-0626b6573061' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b024e6d-14f8-4c2f-8ee7-0626b6573061' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-625364b1-4bdb-4c9d-aa6b-25a372236d6b' class='xr-var-data-in' type='checkbox'><label for='data-625364b1-4bdb-4c9d-aa6b-25a372236d6b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([300., 301., 302., 303., 304., 305., 306., 307., 308., 309., 310., 311.,\n",
       "       312., 313., 314., 315., 316., 317., 318., 319., 320., 321., 322., 323.,\n",
       "       324., 325., 326., 327., 328., 329., 330., 331., 332., 333., 334., 335.,\n",
       "       336., 337., 338., 339., 340., 341., 342., 343., 344., 345., 346., 347.,\n",
       "       348., 349., 350., 351., 352., 353., 354., 355., 356., 357., 358., 359.],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 21.0 22.0 ... 68.0 69.0 70.0</div><input id='attrs-95574038-a249-4b50-b3fc-fda125e5df0b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95574038-a249-4b50-b3fc-fda125e5df0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8128206d-e8c4-47a4-8554-fdd33fdafbdc' class='xr-var-data-in' type='checkbox'><label for='data-8128206d-e8c4-47a4-8554-fdd33fdafbdc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([20., 21., 22., 23., 24., 25., 26., 27., 28., 29., 30., 31., 32., 33.,\n",
       "       34., 35., 36., 37., 38., 39., 40., 41., 42., 43., 44., 45., 46., 47.,\n",
       "       48., 49., 50., 51., 52., 53., 54., 55., 56., 57., 58., 59., 60., 61.,\n",
       "       62., 63., 64., 65., 66., 67., 68., 69., 70.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>plev</span></div><div class='xr-var-dims'>(plev)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>850</div><input id='attrs-7e6fc33c-09ed-4fbf-925c-18ec3703c63f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e6fc33c-09ed-4fbf-925c-18ec3703c63f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47e01e25-91a9-4140-8173-24c002f40292' class='xr-var-data-in' type='checkbox'><label for='data-47e01e25-91a9-4140-8173-24c002f40292' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>millibars</dd><dt><span>long_name :</span></dt><dd>pressure_level</dd></dl></div><div class='xr-var-data'><pre>array([850], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-01-01 ... 2021-02-28</div><input id='attrs-f0c24fed-6dea-4e7b-8eec-af417fac6030' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f0c24fed-6dea-4e7b-8eec-af417fac6030' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0598688-4dd9-4066-9d6c-45901d2339b8' class='xr-var-data-in' type='checkbox'><label for='data-d0598688-4dd9-4066-9d6c-45901d2339b8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T00:00:00.000000000&#x27;, &#x27;2021-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-03T00:00:00.000000000&#x27;, &#x27;2021-01-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-05T00:00:00.000000000&#x27;, &#x27;2021-01-06T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-07T00:00:00.000000000&#x27;, &#x27;2021-01-08T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-09T00:00:00.000000000&#x27;, &#x27;2021-01-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-11T00:00:00.000000000&#x27;, &#x27;2021-01-12T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-13T00:00:00.000000000&#x27;, &#x27;2021-01-14T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-15T00:00:00.000000000&#x27;, &#x27;2021-01-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-17T00:00:00.000000000&#x27;, &#x27;2021-01-18T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-19T00:00:00.000000000&#x27;, &#x27;2021-01-20T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-21T00:00:00.000000000&#x27;, &#x27;2021-01-22T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-23T00:00:00.000000000&#x27;, &#x27;2021-01-24T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-25T00:00:00.000000000&#x27;, &#x27;2021-01-26T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-27T00:00:00.000000000&#x27;, &#x27;2021-01-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-29T00:00:00.000000000&#x27;, &#x27;2021-01-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-31T00:00:00.000000000&#x27;, &#x27;2021-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-02T00:00:00.000000000&#x27;, &#x27;2021-02-03T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-04T00:00:00.000000000&#x27;, &#x27;2021-02-05T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-06T00:00:00.000000000&#x27;, &#x27;2021-02-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-08T00:00:00.000000000&#x27;, &#x27;2021-02-09T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-10T00:00:00.000000000&#x27;, &#x27;2021-02-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-12T00:00:00.000000000&#x27;, &#x27;2021-02-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-14T00:00:00.000000000&#x27;, &#x27;2021-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-16T00:00:00.000000000&#x27;, &#x27;2021-02-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-18T00:00:00.000000000&#x27;, &#x27;2021-02-19T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-20T00:00:00.000000000&#x27;, &#x27;2021-02-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-22T00:00:00.000000000&#x27;, &#x27;2021-02-23T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-24T00:00:00.000000000&#x27;, &#x27;2021-02-25T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-26T00:00:00.000000000&#x27;, &#x27;2021-02-27T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-28T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1d093af9-a948-4925-b539-ebd312490d36' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1d093af9-a948-4925-b539-ebd312490d36' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ua</span></div><div class='xr-var-dims'>(time, plev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-10.78 -9.664 ... 20.13 21.39</div><input id='attrs-ccbd9cc6-22b6-4d2b-b7e1-8cf850f40ad2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ccbd9cc6-22b6-4d2b-b7e1-8cf850f40ad2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0b08a4b-5d2a-41a2-b21a-8145532e1700' class='xr-var-data-in' type='checkbox'><label for='data-d0b08a4b-5d2a-41a2-b21a-8145532e1700' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>U component of wind</dd><dt><span>standard_name :</span></dt><dd>eastward_wind</dd></dl></div><div class='xr-var-data'><pre>array([[[[-10.779781, ...,   6.806973],\n",
       "         ...,\n",
       "         [  2.570747, ...,   4.208183]]],\n",
       "\n",
       "\n",
       "       ...,\n",
       "\n",
       "\n",
       "       [[[-12.231792, ...,  -3.174543],\n",
       "         ...,\n",
       "         [ -0.133591, ...,  21.389854]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>total_area_m2</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.162e+10 1.162e+10 ... 4.229e+09</div><input id='attrs-ae8d0515-9195-459b-af85-e41c9359a720' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ae8d0515-9195-459b-af85-e41c9359a720' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3116454-4875-4cd1-a37d-e676812e418f' class='xr-var-data-in' type='checkbox'><label for='data-e3116454-4875-4cd1-a37d-e676812e418f' 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([[1.16184329e+10, 1.16184329e+10, 1.16187503e+10, ...,\n",
       "        1.16184329e+10, 1.16184329e+10, 1.16184329e+10],\n",
       "       [1.15428613e+10, 1.15428613e+10, 1.15431766e+10, ...,\n",
       "        1.15428613e+10, 1.15428613e+10, 1.15428613e+10],\n",
       "       [1.14637931e+10, 1.14637931e+10, 1.14641063e+10, ...,\n",
       "        1.14637931e+10, 1.14637931e+10, 1.14637931e+10],\n",
       "       ...,\n",
       "       [4.63167292e+09, 4.63167292e+09, 4.63179946e+09, ...,\n",
       "        4.63167292e+09, 4.63167292e+09, 4.63167292e+09],\n",
       "       [4.43089648e+09, 4.43089648e+09, 4.43101754e+09, ...,\n",
       "        4.43089648e+09, 4.43089648e+09, 4.43089648e+09],\n",
       "       [4.22874215e+09, 4.22874215e+09, 4.22885769e+09, ...,\n",
       "        4.22874215e+09, 4.22874215e+09, 4.22874215e+09]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jet_lat</span></div><div class='xr-var-dims'>(time, plev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.2 46.16 42.01 ... 45.94 56.45</div><input id='attrs-ff1945ab-2ad6-4dec-84e1-4cde9dd887bb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ff1945ab-2ad6-4dec-84e1-4cde9dd887bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8979c713-6e2d-4040-8a56-a0f741a65e9d' class='xr-var-data-in' type='checkbox'><label for='data-8979c713-6e2d-4040-8a56-a0f741a65e9d' 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([[46.19632338],\n",
       "       [46.1617058 ],\n",
       "       [42.01034565],\n",
       "       [41.63934638],\n",
       "       [37.41945862],\n",
       "       [37.59902913],\n",
       "       [35.03269566],\n",
       "       [48.66584865],\n",
       "       [47.91574283],\n",
       "       [40.75160235],\n",
       "       [42.44799082],\n",
       "       [45.2446558 ],\n",
       "       [48.10466768],\n",
       "       [44.05784005],\n",
       "       [39.83710043],\n",
       "       [45.11866853],\n",
       "       [44.80010138],\n",
       "       [39.53253256],\n",
       "       [39.05827242],\n",
       "       [40.28587309],\n",
       "...\n",
       "       [44.35057548],\n",
       "       [44.22663739],\n",
       "       [43.62533379],\n",
       "       [44.04237101],\n",
       "       [42.82376168],\n",
       "       [41.75236707],\n",
       "       [43.06920902],\n",
       "       [41.78090481],\n",
       "       [45.10955517],\n",
       "       [42.43873198],\n",
       "       [42.06770106],\n",
       "       [42.24735801],\n",
       "       [41.60133844],\n",
       "       [38.84505967],\n",
       "       [42.96442283],\n",
       "       [44.7225944 ],\n",
       "       [40.82069999],\n",
       "       [41.30061976],\n",
       "       [45.93934268],\n",
       "       [56.45428213]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jet_speed</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.109 3.312 -1.714 ... 6.115 9.825</div><input id='attrs-7edb9771-ad3a-4414-a52f-27f4622f201f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7edb9771-ad3a-4414-a52f-27f4622f201f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d37109e4-9038-4aa2-8d26-4708e79a45c8' class='xr-var-data-in' type='checkbox'><label for='data-d37109e4-9038-4aa2-8d26-4708e79a45c8' 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([ 6.10944462,  3.31196761, -1.71406806, -6.0752883 ,  1.61177254,\n",
       "       -1.45314336, -1.68254626, -4.22817945,  0.47189033,  2.44408822,\n",
       "        5.49302959, 11.24492741, 11.04329205,  7.23249674,  6.09570408,\n",
       "       -0.19672951,  2.60978174, 10.63127041, 11.65985012, 15.82699394,\n",
       "       17.77095222, 18.08460236, 14.12242222, 11.6272831 , 19.08166122,\n",
       "        8.34085655,  9.27634525, 12.62120152, 12.19220638, 17.20098495,\n",
       "       14.24960613, 17.00581551, 14.56629944, 10.9861908 ,  8.91362476,\n",
       "        9.78497696, 10.68161964,  9.97277737, 13.64127254, 22.05234146,\n",
       "       16.66653633, 16.15039253, 18.69407272, 17.13575363, 16.78639603,\n",
       "       11.858634  , 12.99794483, 16.08002472, 18.64548683, 16.53483772,\n",
       "       10.13461876, 10.70244312, 13.7835722 , 15.3696146 , 10.95157909,\n",
       "       10.24378109,  9.02269268,  6.1152935 ,  9.82453442])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7900a7ab-bf13-41b7-9a21-56f7b3f824c2' class='xr-section-summary-in' type='checkbox'  ><label for='section-7900a7ab-bf13-41b7-9a21-56f7b3f824c2' class='xr-section-summary' >Indexes: <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-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-63b530cf-9f58-48ae-b347-c2515f0b9714' class='xr-index-data-in' type='checkbox'/><label for='index-63b530cf-9f58-48ae-b347-c2515f0b9714' 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([300.0, 301.0, 302.0, 303.0, 304.0, 305.0, 306.0, 307.0, 308.0,\n",
       "              309.0, 310.0, 311.0, 312.0, 313.0, 314.0, 315.0, 316.0, 317.0,\n",
       "              318.0, 319.0, 320.0, 321.0, 322.0, 323.0, 324.0, 325.0, 326.0,\n",
       "              327.0, 328.0, 329.0, 330.0, 331.0, 332.0, 333.0, 334.0, 335.0,\n",
       "              336.0, 337.0, 338.0, 339.0, 340.0, 341.0, 342.0, 343.0, 344.0,\n",
       "              345.0, 346.0, 347.0, 348.0, 349.0, 350.0, 351.0, 352.0, 353.0,\n",
       "              354.0, 355.0, 356.0, 357.0, 358.0, 359.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;))</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-100348d8-e798-4192-988e-8faf292c8884' class='xr-index-data-in' type='checkbox'/><label for='index-100348d8-e798-4192-988e-8faf292c8884' 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([20.0, 21.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0,\n",
       "              31.0, 32.0, 33.0, 34.0, 35.0, 36.0, 37.0, 38.0, 39.0, 40.0, 41.0,\n",
       "              42.0, 43.0, 44.0, 45.0, 46.0, 47.0, 48.0, 49.0, 50.0, 51.0, 52.0,\n",
       "              53.0, 54.0, 55.0, 56.0, 57.0, 58.0, 59.0, 60.0, 61.0, 62.0, 63.0,\n",
       "              64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>plev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d172e931-b28b-4de2-a67a-ef76aa6aefc7' class='xr-index-data-in' type='checkbox'/><label for='index-d172e931-b28b-4de2-a67a-ef76aa6aefc7' 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([850], dtype=&#x27;int64&#x27;, name=&#x27;plev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6c442044-1ff3-4698-b69f-baf2b04f95a6' class='xr-index-data-in' type='checkbox'/><label for='index-6c442044-1ff3-4698-b69f-baf2b04f95a6' 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;2021-01-01&#x27;, &#x27;2021-01-02&#x27;, &#x27;2021-01-03&#x27;, &#x27;2021-01-04&#x27;,\n",
       "               &#x27;2021-01-05&#x27;, &#x27;2021-01-06&#x27;, &#x27;2021-01-07&#x27;, &#x27;2021-01-08&#x27;,\n",
       "               &#x27;2021-01-09&#x27;, &#x27;2021-01-10&#x27;, &#x27;2021-01-11&#x27;, &#x27;2021-01-12&#x27;,\n",
       "               &#x27;2021-01-13&#x27;, &#x27;2021-01-14&#x27;, &#x27;2021-01-15&#x27;, &#x27;2021-01-16&#x27;,\n",
       "               &#x27;2021-01-17&#x27;, &#x27;2021-01-18&#x27;, &#x27;2021-01-19&#x27;, &#x27;2021-01-20&#x27;,\n",
       "               &#x27;2021-01-21&#x27;, &#x27;2021-01-22&#x27;, &#x27;2021-01-23&#x27;, &#x27;2021-01-24&#x27;,\n",
       "               &#x27;2021-01-25&#x27;, &#x27;2021-01-26&#x27;, &#x27;2021-01-27&#x27;, &#x27;2021-01-28&#x27;,\n",
       "               &#x27;2021-01-29&#x27;, &#x27;2021-01-30&#x27;, &#x27;2021-01-31&#x27;, &#x27;2021-02-01&#x27;,\n",
       "               &#x27;2021-02-02&#x27;, &#x27;2021-02-03&#x27;, &#x27;2021-02-04&#x27;, &#x27;2021-02-05&#x27;,\n",
       "               &#x27;2021-02-06&#x27;, &#x27;2021-02-07&#x27;, &#x27;2021-02-08&#x27;, &#x27;2021-02-09&#x27;,\n",
       "               &#x27;2021-02-10&#x27;, &#x27;2021-02-11&#x27;, &#x27;2021-02-12&#x27;, &#x27;2021-02-13&#x27;,\n",
       "               &#x27;2021-02-14&#x27;, &#x27;2021-02-15&#x27;, &#x27;2021-02-16&#x27;, &#x27;2021-02-17&#x27;,\n",
       "               &#x27;2021-02-18&#x27;, &#x27;2021-02-19&#x27;, &#x27;2021-02-20&#x27;, &#x27;2021-02-21&#x27;,\n",
       "               &#x27;2021-02-22&#x27;, &#x27;2021-02-23&#x27;, &#x27;2021-02-24&#x27;, &#x27;2021-02-25&#x27;,\n",
       "               &#x27;2021-02-26&#x27;, &#x27;2021-02-27&#x27;, &#x27;2021-02-28&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f1378ce1-8618-44bf-9f0d-685e000cc331' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f1378ce1-8618-44bf-9f0d-685e000cc331' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmwf/mars-client/bin/grib_to_netcdf -S param -o /cache/data6/adaptor.mars.internal-1645789868.3978655-14915-10-d5b8d9d1-2766-4630-b88f-1f6a21a2a0a4.nc /cache/tmp/d5b8d9d1-2766-4630-b88f-1f6a21a2a0a4-adaptor.mars.internal-1645789330.2418482-14915-17-tmp.grib</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:        (lon: 60, lat: 51, plev: 1, time: 59)\n",
       "Coordinates:\n",
       "  * lon            (lon) float32 300.0 301.0 302.0 303.0 ... 357.0 358.0 359.0\n",
       "  * lat            (lat) float32 20.0 21.0 22.0 23.0 ... 67.0 68.0 69.0 70.0\n",
       "  * plev           (plev) int32 850\n",
       "  * time           (time) datetime64[ns] 2021-01-01 2021-01-02 ... 2021-02-28\n",
       "Data variables:\n",
       "    ua             (time, plev, lat, lon) float32 -10.78 -9.664 ... 20.13 21.39\n",
       "    total_area_m2  (lat, lon) float64 1.162e+10 1.162e+10 ... 4.229e+09\n",
       "    jet_lat        (time, plev) float64 46.2 46.16 42.01 ... 41.3 45.94 56.45\n",
       "    jet_speed      (time) float64 6.109 3.312 -1.714 ... 9.023 6.115 9.825\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmw..."
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c18"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e12b2ac-a925-49f9-ae90-cf0a3e1cbbbd",
   "metadata": {},
   "source": [
    "### Zappa et al. 2018"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "64ae8eed-0780-492b-a185-6f99cc88bb8d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 62.4 ms, sys: 0 ns, total: 62.4 ms\n",
      "Wall time: 61.7 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# This takes ~100 milliseconds on Intel i7-10750\n",
    "## For this example we look at only North Atlantic\n",
    "z18 = jsmetrics.jet_statistics.zappa_et_al_2018(\\\n",
    "                    ua.sel(lon=slice(300, 360), lat=slice(70, 20),\\\n",
    "                           plev=slice(850, 850)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "04f5bdb6-c21a-49fb-bc52-fe7a7e7a0d4f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
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       "\n",
       ".xr-attrs dt:hover span {\n",
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       "\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
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       "  display: inline-block;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:        (lon: 60, lat: 51, plev: 1, time: 59)\n",
       "Coordinates:\n",
       "  * lon            (lon) float32 300.0 301.0 302.0 303.0 ... 357.0 358.0 359.0\n",
       "  * lat            (lat) float32 70.0 69.0 68.0 67.0 ... 23.0 22.0 21.0 20.0\n",
       "  * plev           (plev) int32 850\n",
       "  * time           (time) datetime64[ns] 2021-01-01 2021-01-02 ... 2021-02-28\n",
       "Data variables:\n",
       "    ua             (time, plev, lat, lon) float32 2.571 3.133 ... -1.48 -3.175\n",
       "    total_area_m2  (lat, lon) float64 4.229e+09 4.229e+09 ... 1.162e+10\n",
       "    jet_lat        (time, plev) float64 46.68 46.14 41.95 ... 47.7 53.52 60.27\n",
       "    jet_speed      (time) float64 5.634 3.312 0.0 0.0 ... 12.57 11.12 16.32\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmw...</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-6f665f37-3f08-4d39-b48a-5b276f9750cf' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6f665f37-3f08-4d39-b48a-5b276f9750cf' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 60</li><li><span class='xr-has-index'>lat</span>: 51</li><li><span class='xr-has-index'>plev</span>: 1</li><li><span class='xr-has-index'>time</span>: 59</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-2fa4bb1f-e9a7-40a5-ba8a-d99f780eb95e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2fa4bb1f-e9a7-40a5-ba8a-d99f780eb95e' 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'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>300.0 301.0 302.0 ... 358.0 359.0</div><input id='attrs-9144c17e-5d9c-4957-9880-6ac28d31f0a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9144c17e-5d9c-4957-9880-6ac28d31f0a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f33cc857-77c4-4711-b968-a1e13e4e220b' class='xr-var-data-in' type='checkbox'><label for='data-f33cc857-77c4-4711-b968-a1e13e4e220b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([300., 301., 302., 303., 304., 305., 306., 307., 308., 309., 310., 311.,\n",
       "       312., 313., 314., 315., 316., 317., 318., 319., 320., 321., 322., 323.,\n",
       "       324., 325., 326., 327., 328., 329., 330., 331., 332., 333., 334., 335.,\n",
       "       336., 337., 338., 339., 340., 341., 342., 343., 344., 345., 346., 347.,\n",
       "       348., 349., 350., 351., 352., 353., 354., 355., 356., 357., 358., 359.],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>70.0 69.0 68.0 ... 22.0 21.0 20.0</div><input id='attrs-79b9a583-9680-4e6d-a10a-b35050f3ad67' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79b9a583-9680-4e6d-a10a-b35050f3ad67' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6506326e-3930-47f8-94b6-310d4ce623de' class='xr-var-data-in' type='checkbox'><label for='data-6506326e-3930-47f8-94b6-310d4ce623de' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57.,\n",
       "       56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43.,\n",
       "       42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29.,\n",
       "       28., 27., 26., 25., 24., 23., 22., 21., 20.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>plev</span></div><div class='xr-var-dims'>(plev)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>850</div><input id='attrs-14f3341a-61fb-4c93-9cb2-b2f19a8a2ea2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14f3341a-61fb-4c93-9cb2-b2f19a8a2ea2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-009377ba-9720-4e25-98a8-bcca9d95716a' class='xr-var-data-in' type='checkbox'><label for='data-009377ba-9720-4e25-98a8-bcca9d95716a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>millibars</dd><dt><span>long_name :</span></dt><dd>pressure_level</dd></dl></div><div class='xr-var-data'><pre>array([850], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-01-01 ... 2021-02-28</div><input id='attrs-9cd0c6d2-253e-4542-80a8-4da3d393864a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9cd0c6d2-253e-4542-80a8-4da3d393864a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e2a8562-c0c0-4fd1-b2c5-45bc252d8dee' class='xr-var-data-in' type='checkbox'><label for='data-2e2a8562-c0c0-4fd1-b2c5-45bc252d8dee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T00:00:00.000000000&#x27;, &#x27;2021-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-03T00:00:00.000000000&#x27;, &#x27;2021-01-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-05T00:00:00.000000000&#x27;, &#x27;2021-01-06T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-07T00:00:00.000000000&#x27;, &#x27;2021-01-08T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-09T00:00:00.000000000&#x27;, &#x27;2021-01-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-11T00:00:00.000000000&#x27;, &#x27;2021-01-12T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-13T00:00:00.000000000&#x27;, &#x27;2021-01-14T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-15T00:00:00.000000000&#x27;, &#x27;2021-01-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-17T00:00:00.000000000&#x27;, &#x27;2021-01-18T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-19T00:00:00.000000000&#x27;, &#x27;2021-01-20T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-21T00:00:00.000000000&#x27;, &#x27;2021-01-22T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-23T00:00:00.000000000&#x27;, &#x27;2021-01-24T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-25T00:00:00.000000000&#x27;, &#x27;2021-01-26T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-27T00:00:00.000000000&#x27;, &#x27;2021-01-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-29T00:00:00.000000000&#x27;, &#x27;2021-01-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-31T00:00:00.000000000&#x27;, &#x27;2021-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-02T00:00:00.000000000&#x27;, &#x27;2021-02-03T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-04T00:00:00.000000000&#x27;, &#x27;2021-02-05T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-06T00:00:00.000000000&#x27;, &#x27;2021-02-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-08T00:00:00.000000000&#x27;, &#x27;2021-02-09T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-10T00:00:00.000000000&#x27;, &#x27;2021-02-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-12T00:00:00.000000000&#x27;, &#x27;2021-02-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-14T00:00:00.000000000&#x27;, &#x27;2021-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-16T00:00:00.000000000&#x27;, &#x27;2021-02-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-18T00:00:00.000000000&#x27;, &#x27;2021-02-19T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-20T00:00:00.000000000&#x27;, &#x27;2021-02-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-22T00:00:00.000000000&#x27;, &#x27;2021-02-23T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-24T00:00:00.000000000&#x27;, &#x27;2021-02-25T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-26T00:00:00.000000000&#x27;, &#x27;2021-02-27T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-28T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-769e13a9-eae0-4a1a-9e49-624a7b4167b1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-769e13a9-eae0-4a1a-9e49-624a7b4167b1' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ua</span></div><div class='xr-var-dims'>(time, plev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>2.571 3.133 3.281 ... -1.48 -3.175</div><input id='attrs-0c047bd0-d253-441d-8e4b-47d32921e1d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c047bd0-d253-441d-8e4b-47d32921e1d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b575645-17ca-4e1b-a211-a9a088e6e0fd' class='xr-var-data-in' type='checkbox'><label for='data-5b575645-17ca-4e1b-a211-a9a088e6e0fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>U component of wind</dd><dt><span>standard_name :</span></dt><dd>eastward_wind</dd></dl></div><div class='xr-var-data'><pre>array([[[[  2.570747, ...,   4.208183],\n",
       "         ...,\n",
       "         [-10.779781, ...,   6.806973]]],\n",
       "\n",
       "\n",
       "       ...,\n",
       "\n",
       "\n",
       "       [[[ -0.133591, ...,  21.389854],\n",
       "         ...,\n",
       "         [-12.231792, ...,  -3.174543]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>total_area_m2</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.229e+09 4.229e+09 ... 1.162e+10</div><input id='attrs-52e50958-0b20-4927-9c50-9dcb54b19540' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-52e50958-0b20-4927-9c50-9dcb54b19540' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d226a73-c5d9-45b7-b927-fd877aa6fad2' class='xr-var-data-in' type='checkbox'><label for='data-8d226a73-c5d9-45b7-b927-fd877aa6fad2' 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([[4.22874215e+09, 4.22874215e+09, 4.22885769e+09, ...,\n",
       "        4.22874215e+09, 4.22874215e+09, 4.22874215e+09],\n",
       "       [4.43089648e+09, 4.43089648e+09, 4.43101754e+09, ...,\n",
       "        4.43089648e+09, 4.43089648e+09, 4.43089648e+09],\n",
       "       [4.63167292e+09, 4.63167292e+09, 4.63179946e+09, ...,\n",
       "        4.63167292e+09, 4.63167292e+09, 4.63167292e+09],\n",
       "       ...,\n",
       "       [1.14637931e+10, 1.14637931e+10, 1.14641063e+10, ...,\n",
       "        1.14637931e+10, 1.14637931e+10, 1.14637931e+10],\n",
       "       [1.15428613e+10, 1.15428613e+10, 1.15431766e+10, ...,\n",
       "        1.15428613e+10, 1.15428613e+10, 1.15428613e+10],\n",
       "       [1.16184329e+10, 1.16184329e+10, 1.16187503e+10, ...,\n",
       "        1.16184329e+10, 1.16184329e+10, 1.16184329e+10]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jet_lat</span></div><div class='xr-var-dims'>(time, plev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>46.68 46.14 41.95 ... 53.52 60.27</div><input id='attrs-365136a8-e889-4b7b-81fb-21db6f7c3caf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-365136a8-e889-4b7b-81fb-21db6f7c3caf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79491f5f-2c8b-42d8-a9be-eff4db460f41' class='xr-var-data-in' type='checkbox'><label for='data-79491f5f-2c8b-42d8-a9be-eff4db460f41' 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([[46.68438481],\n",
       "       [46.13624069],\n",
       "       [41.95348419],\n",
       "       [40.17559393],\n",
       "       [34.66786405],\n",
       "       [33.65224933],\n",
       "       [32.41600823],\n",
       "       [48.74758689],\n",
       "       [48.36209963],\n",
       "       [44.80700337],\n",
       "       [45.88681407],\n",
       "       [46.54109378],\n",
       "       [49.09258558],\n",
       "       [47.7545397 ],\n",
       "       [46.9225164 ],\n",
       "       [50.37937599],\n",
       "       [51.408574  ],\n",
       "       [42.47228057],\n",
       "       [41.07313643],\n",
       "       [38.79474817],\n",
       "...\n",
       "       [40.20557181],\n",
       "       [39.76091031],\n",
       "       [40.56002669],\n",
       "       [41.40693544],\n",
       "       [40.77865316],\n",
       "       [42.71384511],\n",
       "       [46.04815037],\n",
       "       [46.1149783 ],\n",
       "       [47.12825059],\n",
       "       [43.0606521 ],\n",
       "       [42.28957157],\n",
       "       [41.7372544 ],\n",
       "       [40.5810795 ],\n",
       "       [38.46711808],\n",
       "       [43.27853686],\n",
       "       [47.43395479],\n",
       "       [44.99380032],\n",
       "       [47.70356399],\n",
       "       [53.51808346],\n",
       "       [60.27148823]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jet_speed</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.634 3.312 0.0 ... 11.12 16.32</div><input id='attrs-9f300842-8c13-41f8-8ad9-61c99be2293c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9f300842-8c13-41f8-8ad9-61c99be2293c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2da29a34-e3ff-4f2b-a229-164c3a1a2405' class='xr-var-data-in' type='checkbox'><label for='data-2da29a34-e3ff-4f2b-a229-164c3a1a2405' 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([ 5.63376141,  3.31196761,  0.        ,  0.        ,  8.40504074,\n",
       "       10.81788349,  8.33557892,  0.        ,  0.47189033,  2.61020923,\n",
       "        3.62148333, 13.9708519 , 11.47951412,  4.85284138,  4.10444117,\n",
       "        4.90195465,  0.        , 11.45384026, 12.79873466, 16.65079689,\n",
       "       13.55807018, 17.59778976, 14.44534683, 15.19997501, 18.37319756,\n",
       "       15.01902103, 11.78494072, 11.60702801, 13.56662655, 20.99062347,\n",
       "       14.24960613, 17.00581551, 14.58141899,  9.34975529,  9.95133591,\n",
       "        7.98465157,  8.70756817, 15.18537903, 13.8362999 , 23.0808754 ,\n",
       "       19.94544792, 18.00348854, 19.43610382, 17.09462738, 16.52509117,\n",
       "       12.79683113, 15.74212551, 12.65966606, 18.8422718 , 16.53483772,\n",
       "       10.13461876, 12.24617004, 13.51813126, 15.3696146 , 12.26842117,\n",
       "       11.26608562, 12.57479858, 11.11622524, 16.3225975 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6059c72f-9fd8-4d63-ae58-7cf0b8c1f4a5' class='xr-section-summary-in' type='checkbox'  ><label for='section-6059c72f-9fd8-4d63-ae58-7cf0b8c1f4a5' class='xr-section-summary' >Indexes: <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-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bb1a9842-4e73-4e23-bc23-a907bf001d3c' class='xr-index-data-in' type='checkbox'/><label for='index-bb1a9842-4e73-4e23-bc23-a907bf001d3c' 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([300.0, 301.0, 302.0, 303.0, 304.0, 305.0, 306.0, 307.0, 308.0,\n",
       "              309.0, 310.0, 311.0, 312.0, 313.0, 314.0, 315.0, 316.0, 317.0,\n",
       "              318.0, 319.0, 320.0, 321.0, 322.0, 323.0, 324.0, 325.0, 326.0,\n",
       "              327.0, 328.0, 329.0, 330.0, 331.0, 332.0, 333.0, 334.0, 335.0,\n",
       "              336.0, 337.0, 338.0, 339.0, 340.0, 341.0, 342.0, 343.0, 344.0,\n",
       "              345.0, 346.0, 347.0, 348.0, 349.0, 350.0, 351.0, 352.0, 353.0,\n",
       "              354.0, 355.0, 356.0, 357.0, 358.0, 359.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;))</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-d325822a-c446-46a2-8b96-17cb86e0c4cd' class='xr-index-data-in' type='checkbox'/><label for='index-d325822a-c446-46a2-8b96-17cb86e0c4cd' 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([70.0, 69.0, 68.0, 67.0, 66.0, 65.0, 64.0, 63.0, 62.0, 61.0, 60.0,\n",
       "              59.0, 58.0, 57.0, 56.0, 55.0, 54.0, 53.0, 52.0, 51.0, 50.0, 49.0,\n",
       "              48.0, 47.0, 46.0, 45.0, 44.0, 43.0, 42.0, 41.0, 40.0, 39.0, 38.0,\n",
       "              37.0, 36.0, 35.0, 34.0, 33.0, 32.0, 31.0, 30.0, 29.0, 28.0, 27.0,\n",
       "              26.0, 25.0, 24.0, 23.0, 22.0, 21.0, 20.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>plev</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e13e4cfc-1fd6-4f8d-bcdd-2b527051be12' class='xr-index-data-in' type='checkbox'/><label for='index-e13e4cfc-1fd6-4f8d-bcdd-2b527051be12' 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([850], dtype=&#x27;int64&#x27;, name=&#x27;plev&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9ab3467b-fc7c-40bf-9513-27871b42e6c4' class='xr-index-data-in' type='checkbox'/><label for='index-9ab3467b-fc7c-40bf-9513-27871b42e6c4' 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;2021-01-01&#x27;, &#x27;2021-01-02&#x27;, &#x27;2021-01-03&#x27;, &#x27;2021-01-04&#x27;,\n",
       "               &#x27;2021-01-05&#x27;, &#x27;2021-01-06&#x27;, &#x27;2021-01-07&#x27;, &#x27;2021-01-08&#x27;,\n",
       "               &#x27;2021-01-09&#x27;, &#x27;2021-01-10&#x27;, &#x27;2021-01-11&#x27;, &#x27;2021-01-12&#x27;,\n",
       "               &#x27;2021-01-13&#x27;, &#x27;2021-01-14&#x27;, &#x27;2021-01-15&#x27;, &#x27;2021-01-16&#x27;,\n",
       "               &#x27;2021-01-17&#x27;, &#x27;2021-01-18&#x27;, &#x27;2021-01-19&#x27;, &#x27;2021-01-20&#x27;,\n",
       "               &#x27;2021-01-21&#x27;, &#x27;2021-01-22&#x27;, &#x27;2021-01-23&#x27;, &#x27;2021-01-24&#x27;,\n",
       "               &#x27;2021-01-25&#x27;, &#x27;2021-01-26&#x27;, &#x27;2021-01-27&#x27;, &#x27;2021-01-28&#x27;,\n",
       "               &#x27;2021-01-29&#x27;, &#x27;2021-01-30&#x27;, &#x27;2021-01-31&#x27;, &#x27;2021-02-01&#x27;,\n",
       "               &#x27;2021-02-02&#x27;, &#x27;2021-02-03&#x27;, &#x27;2021-02-04&#x27;, &#x27;2021-02-05&#x27;,\n",
       "               &#x27;2021-02-06&#x27;, &#x27;2021-02-07&#x27;, &#x27;2021-02-08&#x27;, &#x27;2021-02-09&#x27;,\n",
       "               &#x27;2021-02-10&#x27;, &#x27;2021-02-11&#x27;, &#x27;2021-02-12&#x27;, &#x27;2021-02-13&#x27;,\n",
       "               &#x27;2021-02-14&#x27;, &#x27;2021-02-15&#x27;, &#x27;2021-02-16&#x27;, &#x27;2021-02-17&#x27;,\n",
       "               &#x27;2021-02-18&#x27;, &#x27;2021-02-19&#x27;, &#x27;2021-02-20&#x27;, &#x27;2021-02-21&#x27;,\n",
       "               &#x27;2021-02-22&#x27;, &#x27;2021-02-23&#x27;, &#x27;2021-02-24&#x27;, &#x27;2021-02-25&#x27;,\n",
       "               &#x27;2021-02-26&#x27;, &#x27;2021-02-27&#x27;, &#x27;2021-02-28&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-aa896e15-f53b-400f-91fb-60acf1f8f981' class='xr-section-summary-in' type='checkbox'  checked><label for='section-aa896e15-f53b-400f-91fb-60acf1f8f981' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmwf/mars-client/bin/grib_to_netcdf -S param -o /cache/data6/adaptor.mars.internal-1645789868.3978655-14915-10-d5b8d9d1-2766-4630-b88f-1f6a21a2a0a4.nc /cache/tmp/d5b8d9d1-2766-4630-b88f-1f6a21a2a0a4-adaptor.mars.internal-1645789330.2418482-14915-17-tmp.grib</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:        (lon: 60, lat: 51, plev: 1, time: 59)\n",
       "Coordinates:\n",
       "  * lon            (lon) float32 300.0 301.0 302.0 303.0 ... 357.0 358.0 359.0\n",
       "  * lat            (lat) float32 70.0 69.0 68.0 67.0 ... 23.0 22.0 21.0 20.0\n",
       "  * plev           (plev) int32 850\n",
       "  * time           (time) datetime64[ns] 2021-01-01 2021-01-02 ... 2021-02-28\n",
       "Data variables:\n",
       "    ua             (time, plev, lat, lon) float32 2.571 3.133 ... -1.48 -3.175\n",
       "    total_area_m2  (lat, lon) float64 4.229e+09 4.229e+09 ... 1.162e+10\n",
       "    jet_lat        (time, plev) float64 46.68 46.14 41.95 ... 47.7 53.52 60.27\n",
       "    jet_speed      (time) float64 5.634 3.312 0.0 0.0 ... 12.57 11.12 16.32\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmw..."
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z18"
   ]
  },
  {
   "cell_type": "markdown",
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   "metadata": {},
   "source": [
    "### Kerr et al. 2020"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "63207474-5ea3-4e69-809c-3533eb8a0f43",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 334 ms, sys: 1.45 ms, total: 335 ms\n",
      "Wall time: 335 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "# This takes ~450 milliseconds on Intel i7-10750\n",
    "## For this example we look at only North Atlantic\n",
    "k20 = jsmetrics.jet_statistics.kerr_et_al_2020(\\\n",
    "                    ua.sel(lon=slice(300, 360), lat=slice(70, 20),\\\n",
    "                           plev=slice(700, 700)))"
   ]
  },
  {
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   "execution_count": 25,
   "id": "a74b4cb9-1a2a-4da9-93c7-2837d883f8c1",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:           (lon: 60, lat: 51, time: 59)\n",
       "Coordinates:\n",
       "  * lon               (lon) float32 300.0 301.0 302.0 ... 357.0 358.0 359.0\n",
       "  * lat               (lat) float32 20.0 21.0 22.0 23.0 ... 67.0 68.0 69.0 70.0\n",
       "    plev              int32 700\n",
       "  * time              (time) datetime64[ns] 2021-01-01 2021-01-02 ... 2021-02-28\n",
       "Data variables:\n",
       "    ua                (time, lat, lon) float32 -6.866 -6.221 ... 26.31 26.74\n",
       "    jet_lat           (time, lon) float32 43.0 44.0 44.0 44.0 ... 67.0 67.0 67.0\n",
       "    smoothed_jet_lat  (time, lon) float32 nan nan nan nan ... nan nan nan nan\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmw...</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-429a16a2-005f-418c-940d-b215d1fe32a0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-429a16a2-005f-418c-940d-b215d1fe32a0' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 60</li><li><span class='xr-has-index'>lat</span>: 51</li><li><span class='xr-has-index'>time</span>: 59</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-590296af-e6fa-4c92-8301-3e12a47c24ca' class='xr-section-summary-in' type='checkbox'  checked><label for='section-590296af-e6fa-4c92-8301-3e12a47c24ca' 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'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>300.0 301.0 302.0 ... 358.0 359.0</div><input id='attrs-4798ea9f-4bcb-461a-8ad8-ba3060bada82' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4798ea9f-4bcb-461a-8ad8-ba3060bada82' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d25d577-c28f-40a5-9288-a856353fcb4c' class='xr-var-data-in' type='checkbox'><label for='data-5d25d577-c28f-40a5-9288-a856353fcb4c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([300., 301., 302., 303., 304., 305., 306., 307., 308., 309., 310., 311.,\n",
       "       312., 313., 314., 315., 316., 317., 318., 319., 320., 321., 322., 323.,\n",
       "       324., 325., 326., 327., 328., 329., 330., 331., 332., 333., 334., 335.,\n",
       "       336., 337., 338., 339., 340., 341., 342., 343., 344., 345., 346., 347.,\n",
       "       348., 349., 350., 351., 352., 353., 354., 355., 356., 357., 358., 359.],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 21.0 22.0 ... 68.0 69.0 70.0</div><input id='attrs-07b3d385-03d2-425f-a03f-403663cafaad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-07b3d385-03d2-425f-a03f-403663cafaad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5fd3d10c-d5d0-4eb0-9150-17d889e64029' class='xr-var-data-in' type='checkbox'><label for='data-5fd3d10c-d5d0-4eb0-9150-17d889e64029' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([20., 21., 22., 23., 24., 25., 26., 27., 28., 29., 30., 31., 32., 33.,\n",
       "       34., 35., 36., 37., 38., 39., 40., 41., 42., 43., 44., 45., 46., 47.,\n",
       "       48., 49., 50., 51., 52., 53., 54., 55., 56., 57., 58., 59., 60., 61.,\n",
       "       62., 63., 64., 65., 66., 67., 68., 69., 70.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>plev</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>700</div><input id='attrs-415fe5c9-2323-48ee-a015-c2f88ed5aea7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-415fe5c9-2323-48ee-a015-c2f88ed5aea7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9af72efe-a282-4c94-97bc-bf5c42cbd1d0' class='xr-var-data-in' type='checkbox'><label for='data-9af72efe-a282-4c94-97bc-bf5c42cbd1d0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>millibars</dd><dt><span>long_name :</span></dt><dd>pressure_level</dd></dl></div><div class='xr-var-data'><pre>array(700, dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-01-01 ... 2021-02-28</div><input id='attrs-96e89f3a-5fa3-480e-b882-6c94b6c62efa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96e89f3a-5fa3-480e-b882-6c94b6c62efa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a98c4105-0a51-4bb0-bd2b-0142c38d51de' class='xr-var-data-in' type='checkbox'><label for='data-a98c4105-0a51-4bb0-bd2b-0142c38d51de' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-01-01T00:00:00.000000000&#x27;, &#x27;2021-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-03T00:00:00.000000000&#x27;, &#x27;2021-01-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-05T00:00:00.000000000&#x27;, &#x27;2021-01-06T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-07T00:00:00.000000000&#x27;, &#x27;2021-01-08T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-09T00:00:00.000000000&#x27;, &#x27;2021-01-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-11T00:00:00.000000000&#x27;, &#x27;2021-01-12T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-13T00:00:00.000000000&#x27;, &#x27;2021-01-14T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-15T00:00:00.000000000&#x27;, &#x27;2021-01-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-17T00:00:00.000000000&#x27;, &#x27;2021-01-18T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-19T00:00:00.000000000&#x27;, &#x27;2021-01-20T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-21T00:00:00.000000000&#x27;, &#x27;2021-01-22T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-23T00:00:00.000000000&#x27;, &#x27;2021-01-24T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-25T00:00:00.000000000&#x27;, &#x27;2021-01-26T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-27T00:00:00.000000000&#x27;, &#x27;2021-01-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-29T00:00:00.000000000&#x27;, &#x27;2021-01-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-31T00:00:00.000000000&#x27;, &#x27;2021-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-02T00:00:00.000000000&#x27;, &#x27;2021-02-03T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-04T00:00:00.000000000&#x27;, &#x27;2021-02-05T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-06T00:00:00.000000000&#x27;, &#x27;2021-02-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-08T00:00:00.000000000&#x27;, &#x27;2021-02-09T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-10T00:00:00.000000000&#x27;, &#x27;2021-02-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-12T00:00:00.000000000&#x27;, &#x27;2021-02-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-14T00:00:00.000000000&#x27;, &#x27;2021-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-16T00:00:00.000000000&#x27;, &#x27;2021-02-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-18T00:00:00.000000000&#x27;, &#x27;2021-02-19T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-20T00:00:00.000000000&#x27;, &#x27;2021-02-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-22T00:00:00.000000000&#x27;, &#x27;2021-02-23T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-24T00:00:00.000000000&#x27;, &#x27;2021-02-25T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-26T00:00:00.000000000&#x27;, &#x27;2021-02-27T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-02-28T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bcae264a-aab6-4acc-a11c-53585792e677' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bcae264a-aab6-4acc-a11c-53585792e677' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ua</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-6.866 -6.221 -5.24 ... 26.31 26.74</div><input id='attrs-d39b63a4-283a-4746-bc28-03e2453a2e00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d39b63a4-283a-4746-bc28-03e2453a2e00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94353aa7-363e-41ce-a80d-175e022fd896' class='xr-var-data-in' type='checkbox'><label for='data-94353aa7-363e-41ce-a80d-175e022fd896' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>long_name :</span></dt><dd>U component of wind</dd><dt><span>standard_name :</span></dt><dd>eastward_wind</dd></dl></div><div class='xr-var-data'><pre>array([[[-6.8659077e+00, -6.2212029e+00, -5.2398815e+00, ...,\n",
       "          1.3042923e+01,  1.1576648e+01,  1.0894857e+01],\n",
       "        [-7.2025223e+00, -6.2554340e+00, -4.6978722e+00, ...,\n",
       "          1.7692787e+01,  1.6908300e+01,  1.5133935e+01],\n",
       "        [-5.7134266e+00, -4.4268684e+00, -3.1346054e+00, ...,\n",
       "          2.1298569e+01,  2.0205994e+01,  1.9772388e+01],\n",
       "        ...,\n",
       "        [ 5.3150215e+00,  5.8855572e+00,  6.4789143e+00, ...,\n",
       "          3.5263939e+00,  3.1184616e+00,  2.3168583e+00],\n",
       "        [ 8.3631897e-01,  1.2784843e+00,  2.0686760e+00, ...,\n",
       "          1.1986103e+00,  1.2813377e+00,  1.0673866e+00],\n",
       "        [-3.3898354e-01,  5.5961037e-01,  1.1786404e+00, ...,\n",
       "          7.1802139e-02, -2.9904556e-01, -2.9048729e-01]],\n",
       "\n",
       "       [[-8.0355053e+00, -7.2795448e+00, -6.4351540e+00, ...,\n",
       "          1.5601774e+01,  1.6252184e+01,  1.7136515e+01],\n",
       "        [-9.2535973e+00, -7.8871651e+00, -6.7917385e+00, ...,\n",
       "          1.3984306e+01,  1.4797319e+01,  1.5741555e+01],\n",
       "        [-1.1005142e+01, -8.7058830e+00, -7.0627422e+00, ...,\n",
       "          1.0201657e+01,  1.1317054e+01,  1.2569379e+01],\n",
       "...\n",
       "        [-2.9862671e+00, -2.2217503e+00, -1.2261658e+00, ...,\n",
       "          1.4914279e+01,  1.5775787e+01,  1.5972622e+01],\n",
       "        [-3.0290565e+00, -2.2303085e+00, -2.1589909e+00, ...,\n",
       "          1.0792161e+01,  1.1596616e+01,  1.2492356e+01],\n",
       "        [-2.5355434e+00, -2.5954494e+00, -3.3713779e+00, ...,\n",
       "          7.5429630e+00,  7.6913013e+00,  7.8424940e+00]],\n",
       "\n",
       "       [[-1.0440311e+01, -1.0494511e+01, -1.0511627e+01, ...,\n",
       "          1.4553509e+00,  1.3555069e+00,  2.2940369e+00],\n",
       "        [-9.2051010e+00, -9.0653191e+00, -8.8314018e+00, ...,\n",
       "          1.9574223e+00,  8.8196182e-01,  6.9653893e-01],\n",
       "        [-8.2009602e+00, -6.9486351e+00, -6.1185055e+00, ...,\n",
       "          2.3710594e+00,  1.9231892e+00,  1.6594124e-01],\n",
       "        ...,\n",
       "        [ 7.7070808e-01,  9.7039604e-01,  1.3440971e+00, ...,\n",
       "          2.8338976e+01,  2.9380203e+01,  3.0224594e+01],\n",
       "        [-1.6854458e+00, -1.5542240e+00, -1.3288612e+00, ...,\n",
       "          2.5631786e+01,  2.6270784e+01,  2.6621664e+01],\n",
       "        [-3.2087765e+00, -2.7780209e+00, -2.2160435e+00, ...,\n",
       "          2.5483446e+01,  2.6313576e+01,  2.6744329e+01]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jet_lat</span></div><div class='xr-var-dims'>(time, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>43.0 44.0 44.0 ... 67.0 67.0 67.0</div><input id='attrs-8c4a2673-f247-419f-8cc7-811264dd0d9f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c4a2673-f247-419f-8cc7-811264dd0d9f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6be9e54-0695-4c61-8635-563fc4ea344e' class='xr-var-data-in' type='checkbox'><label for='data-a6be9e54-0695-4c61-8635-563fc4ea344e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([[43., 44., 44., ..., 22., 22., 22.],\n",
       "       [47., 47., 45., ..., 34., 34., 34.],\n",
       "       [40., 40., 40., ..., 33., 33., 35.],\n",
       "       ...,\n",
       "       [42., 41., 42., ..., 60., 61., 61.],\n",
       "       [34., 34., 35., ..., 62., 63., 63.],\n",
       "       [57., 49., 48., ..., 67., 67., 67.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>smoothed_jet_lat</span></div><div class='xr-var-dims'>(time, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c6dea090-9f8c-48be-8735-e631a33710fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c6dea090-9f8c-48be-8735-e631a33710fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7257fc8c-f017-46a7-bebe-1cbf3cfa6251' class='xr-var-data-in' type='checkbox'><label for='data-7257fc8c-f017-46a7-bebe-1cbf3cfa6251' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., 22., 22., 22.],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, 35.],\n",
       "       ...,\n",
       "       [42., nan, 42., ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, 49., nan, ..., nan, nan, nan]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-546de9b2-f8d5-4487-9c4b-e58e10583b2b' class='xr-section-summary-in' type='checkbox'  ><label for='section-546de9b2-f8d5-4487-9c4b-e58e10583b2b' 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-d007be19-fb31-47f8-851c-59b922d89277' class='xr-index-data-in' type='checkbox'/><label for='index-d007be19-fb31-47f8-851c-59b922d89277' 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([300.0, 301.0, 302.0, 303.0, 304.0, 305.0, 306.0, 307.0, 308.0,\n",
       "              309.0, 310.0, 311.0, 312.0, 313.0, 314.0, 315.0, 316.0, 317.0,\n",
       "              318.0, 319.0, 320.0, 321.0, 322.0, 323.0, 324.0, 325.0, 326.0,\n",
       "              327.0, 328.0, 329.0, 330.0, 331.0, 332.0, 333.0, 334.0, 335.0,\n",
       "              336.0, 337.0, 338.0, 339.0, 340.0, 341.0, 342.0, 343.0, 344.0,\n",
       "              345.0, 346.0, 347.0, 348.0, 349.0, 350.0, 351.0, 352.0, 353.0,\n",
       "              354.0, 355.0, 356.0, 357.0, 358.0, 359.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;))</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-60fad573-072b-45d1-96e8-670e3ddbcd35' class='xr-index-data-in' type='checkbox'/><label for='index-60fad573-072b-45d1-96e8-670e3ddbcd35' 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([20.0, 21.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0,\n",
       "              31.0, 32.0, 33.0, 34.0, 35.0, 36.0, 37.0, 38.0, 39.0, 40.0, 41.0,\n",
       "              42.0, 43.0, 44.0, 45.0, 46.0, 47.0, 48.0, 49.0, 50.0, 51.0, 52.0,\n",
       "              53.0, 54.0, 55.0, 56.0, 57.0, 58.0, 59.0, 60.0, 61.0, 62.0, 63.0,\n",
       "              64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cd0f0ed5-f3e9-4fb8-b0ce-5779060137d2' class='xr-index-data-in' type='checkbox'/><label for='index-cd0f0ed5-f3e9-4fb8-b0ce-5779060137d2' 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;2021-01-01&#x27;, &#x27;2021-01-02&#x27;, &#x27;2021-01-03&#x27;, &#x27;2021-01-04&#x27;,\n",
       "               &#x27;2021-01-05&#x27;, &#x27;2021-01-06&#x27;, &#x27;2021-01-07&#x27;, &#x27;2021-01-08&#x27;,\n",
       "               &#x27;2021-01-09&#x27;, &#x27;2021-01-10&#x27;, &#x27;2021-01-11&#x27;, &#x27;2021-01-12&#x27;,\n",
       "               &#x27;2021-01-13&#x27;, &#x27;2021-01-14&#x27;, &#x27;2021-01-15&#x27;, &#x27;2021-01-16&#x27;,\n",
       "               &#x27;2021-01-17&#x27;, &#x27;2021-01-18&#x27;, &#x27;2021-01-19&#x27;, &#x27;2021-01-20&#x27;,\n",
       "               &#x27;2021-01-21&#x27;, &#x27;2021-01-22&#x27;, &#x27;2021-01-23&#x27;, &#x27;2021-01-24&#x27;,\n",
       "               &#x27;2021-01-25&#x27;, &#x27;2021-01-26&#x27;, &#x27;2021-01-27&#x27;, &#x27;2021-01-28&#x27;,\n",
       "               &#x27;2021-01-29&#x27;, &#x27;2021-01-30&#x27;, &#x27;2021-01-31&#x27;, &#x27;2021-02-01&#x27;,\n",
       "               &#x27;2021-02-02&#x27;, &#x27;2021-02-03&#x27;, &#x27;2021-02-04&#x27;, &#x27;2021-02-05&#x27;,\n",
       "               &#x27;2021-02-06&#x27;, &#x27;2021-02-07&#x27;, &#x27;2021-02-08&#x27;, &#x27;2021-02-09&#x27;,\n",
       "               &#x27;2021-02-10&#x27;, &#x27;2021-02-11&#x27;, &#x27;2021-02-12&#x27;, &#x27;2021-02-13&#x27;,\n",
       "               &#x27;2021-02-14&#x27;, &#x27;2021-02-15&#x27;, &#x27;2021-02-16&#x27;, &#x27;2021-02-17&#x27;,\n",
       "               &#x27;2021-02-18&#x27;, &#x27;2021-02-19&#x27;, &#x27;2021-02-20&#x27;, &#x27;2021-02-21&#x27;,\n",
       "               &#x27;2021-02-22&#x27;, &#x27;2021-02-23&#x27;, &#x27;2021-02-24&#x27;, &#x27;2021-02-25&#x27;,\n",
       "               &#x27;2021-02-26&#x27;, &#x27;2021-02-27&#x27;, &#x27;2021-02-28&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e15cfa89-61bb-4ca9-91c6-0c187fc8f71c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e15cfa89-61bb-4ca9-91c6-0c187fc8f71c' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmwf/mars-client/bin/grib_to_netcdf -S param -o /cache/data6/adaptor.mars.internal-1645789868.3978655-14915-10-d5b8d9d1-2766-4630-b88f-1f6a21a2a0a4.nc /cache/tmp/d5b8d9d1-2766-4630-b88f-1f6a21a2a0a4-adaptor.mars.internal-1645789330.2418482-14915-17-tmp.grib</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:           (lon: 60, lat: 51, time: 59)\n",
       "Coordinates:\n",
       "  * lon               (lon) float32 300.0 301.0 302.0 ... 357.0 358.0 359.0\n",
       "  * lat               (lat) float32 20.0 21.0 22.0 23.0 ... 67.0 68.0 69.0 70.0\n",
       "    plev              int32 700\n",
       "  * time              (time) datetime64[ns] 2021-01-01 2021-01-02 ... 2021-02-28\n",
       "Data variables:\n",
       "    ua                (time, lat, lon) float32 -6.866 -6.221 ... 26.31 26.74\n",
       "    jet_lat           (time, lon) float32 43.0 44.0 44.0 44.0 ... 67.0 67.0 67.0\n",
       "    smoothed_jet_lat  (time, lon) float32 nan nan nan nan ... nan nan nan nan\n",
       "Attributes:\n",
       "    Conventions:  CF-1.6\n",
       "    history:      2022-02-25 11:51:26 GMT by grib_to_netcdf-2.24.2: /opt/ecmw..."
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "k20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "64d82d5c-5abe-4321-9034-dd3e9fda75cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f759a9842d0>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "k20['jet_lat'].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd4f59ff-dd84-4eee-9620-f09d2990b79b",
   "metadata": {},
   "source": [
    "## Compare all\n",
    "For this part to work, please run all the previous cells (should take 30 seconds) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "53410cfd-674a-4469-804f-a2bb16809ffc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Jet speed comparison')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w10['jet_speed'].plot()\n",
    "bp13['jet_speed'].plot()\n",
    "gp14['jet_speed'].plot()\n",
    "bp15['jet_speed'].plot()\n",
    "bs17['jet_speed'].plot() ## uses a 10-day running mean\n",
    "plt.hlines(b18['seasonal_JSTR'], plt.gca().get_xlim()[0],  plt.gca().get_xlim()[1])\n",
    "c18['jet_speed'].plot()\n",
    "z18['jet_speed'].plot()\n",
    "plt.legend(['Woollings et al. 2010', 'Barnes & Polvani 2013',\\\n",
    "           'Grise & Polvani 2014', 'Barnes & Polvani 2015',\\\n",
    "           'Barnes & Simpson 2017', 'Bracegirlde et al. 2018',\\\n",
    "            'Ceppi et al. 2018', 'Zappa et al. 2018'], fontsize=8)\n",
    "plt.title('Jet speed comparison')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e4db7a99-41a3-4acd-8525-ae0a44e246aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Jet latitude comparison')"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w10['jet_lat'].plot()\n",
    "bp13['jet_lat'].plot()\n",
    "gp14['jet_lat'].plot()\n",
    "bp15['jet_lat'].plot()\n",
    "bs17['jet_lat'].plot() ## uses a 10-day running mean\n",
    "plt.hlines(b18['seasonal_JPOS'], plt.gca().get_xlim()[0],  plt.gca().get_xlim()[1])\n",
    "c18['jet_lat'].plot()\n",
    "z18['jet_lat'].plot()\n",
    "k20['jet_lat'].mean('lon').plot()\n",
    "plt.legend(['Woollings et al. 2010', 'Barnes & Polvani 2013',\\\n",
    "           'Grise & Polvani 2014', 'Barnes & Polvani 2015',\\\n",
    "           'Barnes & Simpson 2017', 'Bracegirlde et al. 2018',\\\n",
    "            'Ceppi et al. 2018', 'Zappa et al. 2018', 'Kerr et al. 2020'], fontsize=6)\n",
    "plt.title('Jet latitude comparison')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "40e9eaf0-1e6b-45b6-abf6-a8b4207ccfc7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "bd300bb5-08d3-4e49-82d3-daf1bced483b",
   "metadata": {},
   "source": [
    "## Examples in the docs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "1dff21a7-bb7d-4155-9263-3e72eb458871",
   "metadata": {},
   "outputs": [],
   "source": [
    "u_sub = ua.sel(time=slice(\"2021-01\", \"2021-03\"), plev=slice(700, 850), lat=slice(60, 20), lon=slice(135, 235))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "18785b06-54f6-4a8f-b554-5092830e51d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import jsmetrics.metrics.jet_statistics as jet_statistics\n",
    "w10 = jet_statistics.woollings_et_al_2010(u_sub, window_size=20, filter_freq=5)\n",
    "bp13 = jet_statistics.barnes_polvani_2013(u_sub, window_size=20, filter_freq=5)\n",
    "gp14 = jet_statistics.grise_polvani_2014(u_sub)\n",
    "z18 = jet_statistics.zappa_et_al_2018(u_sub)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "b0fd3d5a-9012-4219-b060-180ccf95fb25",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "all_metrics = [w10, bp13, gp14, z18]\n",
    "\n",
    "fig, axes = plt.subplots(1, 2, sharex=True, figsize=(8, 3))\n",
    "for metric in all_metrics:\n",
    "    metric['jet_lat'].plot(ax=axes[0])\n",
    "    metric['jet_speed'].plot(ax=axes[1])\n",
    "\n",
    "axes[0].set_ylabel(\"Mean jet latitude ($\\circ N$)\")\n",
    "axes[1].legend(['Woollings et al. 2010', 'Barnes & Polvani 2013',\\\n",
    "                'Grise & Polvani 2014', 'Zappa et al. 2018'], fontsize=7)\n",
    "axes[1].set_ylabel(\"Mean jet speed ($m s^{-1}$)\")\n",
    "\n",
    "fig.suptitle('Mean jet speed and position of the North Pacific Jet')\n",
    "plt.subplots_adjust(wspace=.3)\n",
    "# fig.savefig('example_jet_speed_and_lat.png', bbox_inches='tight', transparent=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "3a09c229-178a-4cda-8ffa-a3dcd9ef830e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def calc_jet_lat_by_lon(data_row, jet_lat_func):\n",
    "    data_row = data_row.expand_dims('lon')\n",
    "    data_row['jet_lat'] = jet_lat_func(data_row)['jet_lat']\n",
    "    data_row = data_row.isel(lon=0)\n",
    "    data_row = data_row.drop('ua')\n",
    "    return data_row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "38bea032-2a4c-41f4-a0e2-10c40d8dd005",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1min 13s, sys: 907 ms, total: 1min 14s\n",
      "Wall time: 1min 14s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "## Takes 1.2 minutes\n",
    "out = ua.groupby('lon').map(calc_jet_lat_by_lon, (jet_statistics.barnes_polvani_2013,))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "a18e3a60-06e8-4807-bfd1-45820494a203",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(170, 5, 'metric used: Barnes & Polvani 2013')"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1)\n",
    "\n",
    "mean_jet_lat = out['jet_lat'].mean(axis=1)\n",
    "std_jet_lat = out['jet_lat'].std(axis=1).dropna('lon')\n",
    "jet_lons = mean_jet_lat['lon']\n",
    "std2_above = (mean_jet_lat + (std_jet_lat*2))\n",
    "std2_below = (mean_jet_lat - (std_jet_lat*2))\n",
    "\n",
    "mean_jet_lat.plot(ax=ax)\n",
    "ax.fill_between(jet_lons, std2_above, std2_below, alpha=0.2)\n",
    "ax.legend(['mean', '2 std'])\n",
    "ax.set_xlabel(\"Longitude ($\\circ E$)\")\n",
    "ax.set_ylabel(\"Jet latitude ($\\circ N$)\")\n",
    "ax.set_title(\"Estimation of jet position between Jan-Feb 2021\")\n",
    "ax.text(s=\"metric used: Barnes & Polvani 2013\", x=170, y=5, c='grey') \n",
    "# fig.savefig('example_jet_lat_by_lon.png', bbox_inches='tight', transparent=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef100c40-a981-42e1-816a-d6bdb2928ab1",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}