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    "**Brian Blaylock**  \n",
    "*March 14, 2022*\n",
    "\n",
    "# Global Ensembele Forecast System (GEFS) reanalysis: 2000-2019\n",
    "\n",
    "The GEFS version 12 reanalysis is available on [Amazon Web Services ](https://registry.opendata.aws/noaa-gefs-reforecast/) and can be retrieved with Herbie.\n",
    "\n",
    "**The GEFS directory structure is different than other models that Herbie can access, and that makes Herbie's access to these files little awkward.** Instead of grouping the GRIB fields by forecast hour where there are many different variables for the same lead time in the same file, the GEFS files are grouped into the same variable per file with each GRIB message being a different lead time. This changes the way a user would use Herbie to access GEFS data--a user will need to supply a \"variable_level\" argument to access a full file. For subsetting by specific grib messages, you will use the \"searchString\" argument to key in on the message of interest. You will still need to give a value for \"fxx\" to tell Herbie which directory to look for. \n",
    "\n",
    "Yeah, it's a little different paradigm for Herbie, but we can work with it. It may be nice to write a `herbie.tool` to help make calls to Herbie a little more simple (like a custom bulk_download script)"
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    "import cartopy.crs as ccrs\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "from herbie.archive import Herbie\n",
    "\n",
    "# ! The following are imported from\n",
    "# https://github.com/blaylockbk/Carpenter_Workshop\n",
    "from paint.standard2 import cm_tmp, cm_wind, cm_wave_height\n",
    "from toolbox.cartopy_tools import common_features, pc"
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    "## Retrieve a full file\n",
    "Download a full GRIB2 file to your local system.\n",
    "\n",
    "Remember to specify the following:\n",
    "- `fxx` is the lead time lead time, a number between 0 and 384. If you are getting the full file, this only tells Herbie what folder to look in (Days:0-10 or Days:10-16). \n",
    "- `member` is the ensemble member. 0 is the control and a value between 1, 2, 3, or 4 is a perturbation member.\n",
    "- `variable_level` is the name of the file to obtain.\n"
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      "C:\\Users\\blayl_depgywe\\BB_python\\Herbie\\herbie\\archive.py:287: UserWarning: `product` not specified. Will use [\"GEFSv12/reforecast\"].\n",
      "  warnings.warn(f'`product` not specified. Will use [\"{self.product}\"].')\n"
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     "text": [
      "🏋🏻‍♂️ Found \u001b[32m2017-Mar-14 00:00 UTC F12\u001b[m [GEFS] [product=GEFSv12/reforecast] GRIB2 file from \u001b[31mlocal\u001b[m and index file from \u001b[31maws\u001b[m.                                                                                                                                                       \n",
      "🌉 Already have local copy --> C:\\Users\\blayl_depgywe\\data\\gefs\\20170314\\tmp_2m_2017031400_c00.grib2\n"
     ]
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    "H = Herbie(\"2017-03-14\", model=\"gefs\", fxx=12, member=0, variable_level=\"tmp_2m\")\n",
    "H.download()"
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    "## Download/Retrieve a subset\n",
    "\n",
    "Subsetting uses the `searchString` argument to parse out information from the GRIB2's index file. Since the variables of each message in a file are all the same, we need to set the `searchString` to key in on the lead time we are interested in.\n",
    "\n",
    "Look at the index file to see how to key in on a specific GRIB message."
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       "grib_message\n",
       "1.0     :TMP:2 m above ground:3 hour fcst:ENS=low-res ctl\n",
       "2.0     :TMP:2 m above ground:6 hour fcst:ENS=low-res ctl\n",
       "3.0     :TMP:2 m above ground:9 hour fcst:ENS=low-res ctl\n",
       "4.0     :TMP:2 m above ground:12 hour fcst:ENS=low-res...\n",
       "5.0     :TMP:2 m above ground:15 hour fcst:ENS=low-res...\n",
       "                              ...                        \n",
       "76.0    :TMP:2 m above ground:228 hour fcst:ENS=low-re...\n",
       "77.0    :TMP:2 m above ground:231 hour fcst:ENS=low-re...\n",
       "78.0    :TMP:2 m above ground:234 hour fcst:ENS=low-re...\n",
       "79.0    :TMP:2 m above ground:237 hour fcst:ENS=low-re...\n",
       "80.0    :TMP:2 m above ground:240 hour fcst:ENS=low-re...\n",
       "Name: search_this, Length: 80, dtype: object"
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    "# Look at the search_this column of the index DataFrame\n",
    "H.read_idx().search_this"
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   "id": "24b519cd",
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   "source": [
    "# Get the 15-h forecast\n",
    "ds = H.xarray(\":15 hour fcst:\")"
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:              (latitude: 721, longitude: 1440)\n",
       "Coordinates:\n",
       "    number               int32 0\n",
       "    time                 datetime64[ns] 2017-03-14\n",
       "    step                 timedelta64[ns] 15:00:00\n",
       "    heightAboveGround    float64 2.0\n",
       "  * latitude             (latitude) float64 90.0 89.75 89.5 ... -89.75 -90.0\n",
       "  * longitude            (longitude) float64 0.0 0.25 0.5 ... 359.2 359.5 359.8\n",
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       "    gribfile_projection  object None\n",
       "Attributes:\n",
       "    GRIB_edition:            2\n",
       "    GRIB_centre:             kwbc\n",
       "    GRIB_centreDescription:  US National Weather Service - NCEP\n",
       "    GRIB_subCentre:          2\n",
       "    Conventions:             CF-1.7\n",
       "    institution:             US National Weather Service - NCEP\n",
       "    model:                   gefs\n",
       "    product:                 GEFSv12/reforecast\n",
       "    description:             Global Ensemble Forecast System (GEFS)\n",
       "    remote_grib:             C:\\Users\\blayl_depgywe\\data\\gefs\\20170314\\tmp_2m...\n",
       "    local_grib:              C:\\Users\\blayl_depgywe\\data\\gefs\\20170314\\tmp_2m...\n",
       "    searchString:            :15 hour fcst:</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-6db4159a-2914-4272-bbf7-424cc35d89e1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6db4159a-2914-4272-bbf7-424cc35d89e1' 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'>latitude</span>: 721</li><li><span class='xr-has-index'>longitude</span>: 1440</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-1e773522-731d-4b46-8af9-fcf2407848d3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1e773522-731d-4b46-8af9-fcf2407848d3' class='xr-section-summary' >Coordinates: <span>(7)</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>number</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-b4ab0a77-a020-4894-a047-ed7720bf1f6c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b4ab0a77-a020-4894-a047-ed7720bf1f6c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8636221-cfaa-4caf-8360-bdad3b5534c6' class='xr-var-data-in' type='checkbox'><label for='data-f8636221-cfaa-4caf-8360-bdad3b5534c6' title='Show/Hide data 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>ensemble member numerical id</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>standard_name :</span></dt><dd>realization</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2017-03-14</div><input id='attrs-2acc4b30-e124-4cfd-9ff8-5cfd5837f058' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2acc4b30-e124-4cfd-9ff8-5cfd5837f058' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b2cb364-32ea-42cb-b560-e05fb5b65824' class='xr-var-data-in' type='checkbox'><label for='data-7b2cb364-32ea-42cb-b560-e05fb5b65824' title='Show/Hide data 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>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2017-03-14T00:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>15:00:00</div><input id='attrs-df4a4c1b-a8a2-4fb6-891b-1c72eef9499e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-df4a4c1b-a8a2-4fb6-891b-1c72eef9499e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9ebb5011-2575-4646-bc0c-e9a50a38ec4e' class='xr-var-data-in' type='checkbox'><label for='data-9ebb5011-2575-4646-bc0c-e9a50a38ec4e' title='Show/Hide data 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 since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>array(54000000000000, dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heightAboveGround</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-216f9fed-edd9-4e1b-ae46-8ac6167562d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-216f9fed-edd9-4e1b-ae46-8ac6167562d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1afd5653-05cc-4009-bc90-bb2ca72c63b8' class='xr-var-data-in' type='checkbox'><label for='data-1afd5653-05cc-4009-bc90-bb2ca72c63b8' title='Show/Hide data 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>height above the surface</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>90.0 89.75 89.5 ... -89.75 -90.0</div><input id='attrs-f88e7ee4-10be-4e7b-a7e9-787cc99ad168' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f88e7ee4-10be-4e7b-a7e9-787cc99ad168' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b42593f0-20af-47c2-9238-710ceb7d00ee' class='xr-var-data-in' type='checkbox'><label for='data-b42593f0-20af-47c2-9238-710ceb7d00ee' title='Show/Hide data 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>stored_direction :</span></dt><dd>decreasing</dd></dl></div><div class='xr-var-data'><pre>array([ 90.  ,  89.75,  89.5 , ..., -89.5 , -89.75, -90.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.25 0.5 ... 359.2 359.5 359.8</div><input id='attrs-78dede83-2ccb-403a-82a8-bd870f82e1c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78dede83-2ccb-403a-82a8-bd870f82e1c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23421fbb-59e7-4d72-972a-055a02431d7a' class='xr-var-data-in' type='checkbox'><label for='data-23421fbb-59e7-4d72-972a-055a02431d7a' title='Show/Hide data 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([0.0000e+00, 2.5000e-01, 5.0000e-01, ..., 3.5925e+02, 3.5950e+02,\n",
       "       3.5975e+02])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>valid_time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-411b861a-4e44-4d76-a8c5-bf2cfba26c85' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-411b861a-4e44-4d76-a8c5-bf2cfba26c85' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4d262c7-ac61-4a49-a13a-bec6b25ba8e7' class='xr-var-data-in' type='checkbox'><label for='data-d4d262c7-ac61-4a49-a13a-bec6b25ba8e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2017-03-14T15:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-26572590-e631-438a-aba6-72e3c7d368a3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-26572590-e631-438a-aba6-72e3c7d368a3' class='xr-section-summary' >Data variables: <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>t2m</span></div><div class='xr-var-dims'>(latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7fcf1b35-da33-4e43-8f6c-03f40f92630c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7fcf1b35-da33-4e43-8f6c-03f40f92630c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb87cc8b-1005-4ee9-8af9-d78dcf750e48' class='xr-var-data-in' type='checkbox'><label for='data-bb87cc8b-1005-4ee9-8af9-d78dcf750e48' title='Show/Hide data 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>GRIB_paramId :</span></dt><dd>167</dd><dt><span>GRIB_dataType :</span></dt><dd>cf</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>air_temperature</dd><dt><span>GRIB_cfVarName :</span></dt><dd>t2m</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/longitude. Also called equidistant cylindrical, or Plate Carree</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>359.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>9999</dd><dt><span>GRIB_name :</span></dt><dd>2 metre temperature</dd><dt><span>GRIB_parameterName :</span></dt><dd>Temperature</dd><dt><span>GRIB_parameterUnits :</span></dt><dd>K</dd><dt><span>GRIB_shortName :</span></dt><dd>2t</dd><dt><span>GRIB_stepRange :</span></dt><dd>15</dd><dt><span>GRIB_totalNumber :</span></dt><dd>10</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>2 metre temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>grid_mapping :</span></dt><dd>gribfile_projection</dd></dl></div><div class='xr-var-data'><pre>[1038240 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gribfile_projection</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>None</div><input id='attrs-c251a1bf-f5e7-44b3-b74b-db1490b7ed73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c251a1bf-f5e7-44b3-b74b-db1490b7ed73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4fb6505a-d1bd-4a06-9e60-bbc1dc4cd786' class='xr-var-data-in' type='checkbox'><label for='data-4fb6505a-d1bd-4a06-9e60-bbc1dc4cd786' title='Show/Hide data 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>crs_wkt :</span></dt><dd>GEOGCRS[&quot;unknown&quot;,DATUM[&quot;unknown&quot;,ELLIPSOID[&quot;unknown&quot;,6371229,0,LENGTHUNIT[&quot;metre&quot;,1,ID[&quot;EPSG&quot;,9001]]]],PRIMEM[&quot;Greenwich&quot;,0,ANGLEUNIT[&quot;degree&quot;,0.0174532925199433],ID[&quot;EPSG&quot;,8901]],CS[ellipsoidal,2],AXIS[&quot;longitude&quot;,east,ORDER[1],ANGLEUNIT[&quot;degree&quot;,0.0174532925199433,ID[&quot;EPSG&quot;,9122]]],AXIS[&quot;latitude&quot;,north,ORDER[2],ANGLEUNIT[&quot;degree&quot;,0.0174532925199433,ID[&quot;EPSG&quot;,9122]]]]</dd><dt><span>semi_major_axis :</span></dt><dd>6371229.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6371229.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>unknown</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>unknown</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>long_name :</span></dt><dd>GEFS model grid projection</dd></dl></div><div class='xr-var-data'><pre>array(None, dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a9e78b7e-0e54-41db-a2b7-17f5f97eb3a4' class='xr-section-summary-in' type='checkbox'  ><label for='section-a9e78b7e-0e54-41db-a2b7-17f5f97eb3a4' class='xr-section-summary' >Attributes: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>GRIB_edition :</span></dt><dd>2</dd><dt><span>GRIB_centre :</span></dt><dd>kwbc</dd><dt><span>GRIB_centreDescription :</span></dt><dd>US National Weather Service - NCEP</dd><dt><span>GRIB_subCentre :</span></dt><dd>2</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>institution :</span></dt><dd>US National Weather Service - NCEP</dd><dt><span>model :</span></dt><dd>gefs</dd><dt><span>product :</span></dt><dd>GEFSv12/reforecast</dd><dt><span>description :</span></dt><dd>Global Ensemble Forecast System (GEFS)</dd><dt><span>remote_grib :</span></dt><dd>C:\\Users\\blayl_depgywe\\data\\gefs\\20170314\\tmp_2m_2017031400_c00.grib2</dd><dt><span>local_grib :</span></dt><dd>C:\\Users\\blayl_depgywe\\data\\gefs\\20170314\\tmp_2m_2017031400_c00.grib2.subset_ac3478d69a3c81fa62e60f5c3696165a4e5e6ac4</dd><dt><span>searchString :</span></dt><dd>:15 hour fcst:</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:              (latitude: 721, longitude: 1440)\n",
       "Coordinates:\n",
       "    number               int32 0\n",
       "    time                 datetime64[ns] 2017-03-14\n",
       "    step                 timedelta64[ns] 15:00:00\n",
       "    heightAboveGround    float64 2.0\n",
       "  * latitude             (latitude) float64 90.0 89.75 89.5 ... -89.75 -90.0\n",
       "  * longitude            (longitude) float64 0.0 0.25 0.5 ... 359.2 359.5 359.8\n",
       "    valid_time           datetime64[ns] ...\n",
       "Data variables:\n",
       "    t2m                  (latitude, longitude) float32 ...\n",
       "    gribfile_projection  object None\n",
       "Attributes:\n",
       "    GRIB_edition:            2\n",
       "    GRIB_centre:             kwbc\n",
       "    GRIB_centreDescription:  US National Weather Service - NCEP\n",
       "    GRIB_subCentre:          2\n",
       "    Conventions:             CF-1.7\n",
       "    institution:             US National Weather Service - NCEP\n",
       "    model:                   gefs\n",
       "    product:                 GEFSv12/reforecast\n",
       "    description:             Global Ensemble Forecast System (GEFS)\n",
       "    remote_grib:             C:\\Users\\blayl_depgywe\\data\\gefs\\20170314\\tmp_2m...\n",
       "    local_grib:              C:\\Users\\blayl_depgywe\\data\\gefs\\20170314\\tmp_2m...\n",
       "    searchString:            :15 hour fcst:"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2fa1a7d9",
   "metadata": {},
   "source": [
    "## Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4e58339a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\blayl_depgywe\\miniconda3\\envs\\herbie\\lib\\site-packages\\metpy\\xarray.py:353: UserWarning: More than one time coordinate present for variable \"gribfile_projection\".\n",
      "  warnings.warn('More than one ' + axis + ' coordinate present for variable'\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(1.0, 1.0, '2 metre temperature')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = common_features(\"50m\", crs=ds.herbie.crs, figsize=[10, 10]).STATES().BORDERS().ax\n",
    "p = ax.pcolormesh(\n",
    "    ds.longitude, ds.latitude, ds.t2m, transform=pc, **cm_tmp(units=\"K\").cmap_kwargs\n",
    ")\n",
    "plt.colorbar(\n",
    "    p, ax=ax, orientation=\"horizontal\", pad=0.05, **cm_tmp(units=\"K\").cbar_kwargs\n",
    ")\n",
    "\n",
    "ax.set_title(\n",
    "    f\"{ds.model.upper()}: {H.product_description}\\nValid: {ds.valid_time.dt.strftime('%H:%M UTC %d %b %Y').item()}\",\n",
    "    loc=\"left\",\n",
    ")\n",
    "ax.set_title(ds.t2m.GRIB_name, loc=\"right\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e478b63",
   "metadata": {},
   "source": [
    "# What are valid values for `variable_level`?\n",
    "You need to look at the file structure within the GEFS bucket to know what is avaialble. We can use s3fs to tell us what we can use for our `variable_level` argument."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "da8d9a4e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import s3fs\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "69ac8854",
   "metadata": {},
   "outputs": [],
   "source": [
    "# List files in the GEFS bucket for a day\n",
    "fs = s3fs.S3FileSystem(anon=True)\n",
    "files = fs.ls(\n",
    "    path=\"noaa-gefs-retrospective/GEFSv12/reforecast/2015/2015010100/c00/Days:1-10\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b8d2941c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# var_lev prefix\n",
    "var_lev = [i.split(\"/\")[-1].split(\"_\") for i in files if i.endswith(\".grib2\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5446fc7f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>variable</th>\n",
       "      <th>level</th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>acpcp</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>apcp</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>cape</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>cin</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>dlwrf</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>dswrf</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>gflux</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>gust</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>hgt</td>\n",
       "      <td>ceiling</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>hgt</td>\n",
       "      <td>hybr</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>hgt</td>\n",
       "      <td>pres</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>hgt</td>\n",
       "      <td>pres</td>\n",
       "      <td>abv700mb</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>hgt</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>hlcy</td>\n",
       "      <td>hgt</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>lhtfl</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>ncpcp</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>pbl</td>\n",
       "      <td>hgt</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>pres</td>\n",
       "      <td>hybr</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>pres</td>\n",
       "      <td>msl</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>pres</td>\n",
       "      <td>pvor</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>pres</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>pvort</td>\n",
       "      <td>isen</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>pwat</td>\n",
       "      <td>eatm</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>rh</td>\n",
       "      <td>hybr</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>sfcr</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>shtfl</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>soilw</td>\n",
       "      <td>bgrnd</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>spfh</td>\n",
       "      <td>2m</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>spfh</td>\n",
       "      <td>pres</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>spfh</td>\n",
       "      <td>pres</td>\n",
       "      <td>abv700mb</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>tcdc</td>\n",
       "      <td>eatm</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>tmax</td>\n",
       "      <td>2m</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>tmin</td>\n",
       "      <td>2m</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>tmp</td>\n",
       "      <td>2m</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>tmp</td>\n",
       "      <td>hybr</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>tmp</td>\n",
       "      <td>pres</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>tmp</td>\n",
       "      <td>pres</td>\n",
       "      <td>abv700mb</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>tmp</td>\n",
       "      <td>pvor</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>tmp</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>tozne</td>\n",
       "      <td>eatm</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>tsoil</td>\n",
       "      <td>bgrnd</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>uflx</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>ugrd</td>\n",
       "      <td>hgt</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>ugrd</td>\n",
       "      <td>hybr</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>ugrd</td>\n",
       "      <td>pres</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>ugrd</td>\n",
       "      <td>pres</td>\n",
       "      <td>abv700mb</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>ugrd</td>\n",
       "      <td>pvor</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>ulwrf</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>ulwrf</td>\n",
       "      <td>tatm</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>uswrf</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>vflx</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>vgrd</td>\n",
       "      <td>hgt</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>vgrd</td>\n",
       "      <td>hybr</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>vgrd</td>\n",
       "      <td>pres</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>vgrd</td>\n",
       "      <td>pres</td>\n",
       "      <td>abv700mb</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>vgrd</td>\n",
       "      <td>pvor</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>vvel</td>\n",
       "      <td>pres</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>vvel</td>\n",
       "      <td>pres</td>\n",
       "      <td>abv700mb</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>watr</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>weasd</td>\n",
       "      <td>sfc</td>\n",
       "      <td>2015010100</td>\n",
       "      <td>c00.grib2</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   variable    level           a           b          c\n",
       "0     acpcp      sfc  2015010100   c00.grib2       None\n",
       "1      apcp      sfc  2015010100   c00.grib2       None\n",
       "2      cape      sfc  2015010100   c00.grib2       None\n",
       "3       cin      sfc  2015010100   c00.grib2       None\n",
       "4     dlwrf      sfc  2015010100   c00.grib2       None\n",
       "5     dswrf      sfc  2015010100   c00.grib2       None\n",
       "6     gflux      sfc  2015010100   c00.grib2       None\n",
       "7      gust      sfc  2015010100   c00.grib2       None\n",
       "8       hgt  ceiling  2015010100   c00.grib2       None\n",
       "9       hgt     hybr  2015010100   c00.grib2       None\n",
       "10      hgt     pres  2015010100   c00.grib2       None\n",
       "11      hgt     pres    abv700mb  2015010100  c00.grib2\n",
       "12      hgt      sfc  2015010100   c00.grib2       None\n",
       "13     hlcy      hgt  2015010100   c00.grib2       None\n",
       "14    lhtfl      sfc  2015010100   c00.grib2       None\n",
       "15    ncpcp      sfc  2015010100   c00.grib2       None\n",
       "16      pbl      hgt  2015010100   c00.grib2       None\n",
       "17     pres     hybr  2015010100   c00.grib2       None\n",
       "18     pres      msl  2015010100   c00.grib2       None\n",
       "19     pres     pvor  2015010100   c00.grib2       None\n",
       "20     pres      sfc  2015010100   c00.grib2       None\n",
       "21    pvort     isen  2015010100   c00.grib2       None\n",
       "22     pwat     eatm  2015010100   c00.grib2       None\n",
       "23       rh     hybr  2015010100   c00.grib2       None\n",
       "24     sfcr      sfc  2015010100   c00.grib2       None\n",
       "25    shtfl      sfc  2015010100   c00.grib2       None\n",
       "26    soilw    bgrnd  2015010100   c00.grib2       None\n",
       "27     spfh       2m  2015010100   c00.grib2       None\n",
       "28     spfh     pres  2015010100   c00.grib2       None\n",
       "29     spfh     pres    abv700mb  2015010100  c00.grib2\n",
       "30     tcdc     eatm  2015010100   c00.grib2       None\n",
       "31     tmax       2m  2015010100   c00.grib2       None\n",
       "32     tmin       2m  2015010100   c00.grib2       None\n",
       "33      tmp       2m  2015010100   c00.grib2       None\n",
       "34      tmp     hybr  2015010100   c00.grib2       None\n",
       "35      tmp     pres  2015010100   c00.grib2       None\n",
       "36      tmp     pres    abv700mb  2015010100  c00.grib2\n",
       "37      tmp     pvor  2015010100   c00.grib2       None\n",
       "38      tmp      sfc  2015010100   c00.grib2       None\n",
       "39    tozne     eatm  2015010100   c00.grib2       None\n",
       "40    tsoil    bgrnd  2015010100   c00.grib2       None\n",
       "41     uflx      sfc  2015010100   c00.grib2       None\n",
       "42     ugrd      hgt  2015010100   c00.grib2       None\n",
       "43     ugrd     hybr  2015010100   c00.grib2       None\n",
       "44     ugrd     pres  2015010100   c00.grib2       None\n",
       "45     ugrd     pres    abv700mb  2015010100  c00.grib2\n",
       "46     ugrd     pvor  2015010100   c00.grib2       None\n",
       "47    ulwrf      sfc  2015010100   c00.grib2       None\n",
       "48    ulwrf     tatm  2015010100   c00.grib2       None\n",
       "49    uswrf      sfc  2015010100   c00.grib2       None\n",
       "50     vflx      sfc  2015010100   c00.grib2       None\n",
       "51     vgrd      hgt  2015010100   c00.grib2       None\n",
       "52     vgrd     hybr  2015010100   c00.grib2       None\n",
       "53     vgrd     pres  2015010100   c00.grib2       None\n",
       "54     vgrd     pres    abv700mb  2015010100  c00.grib2\n",
       "55     vgrd     pvor  2015010100   c00.grib2       None\n",
       "56     vvel     pres  2015010100   c00.grib2       None\n",
       "57     vvel     pres    abv700mb  2015010100  c00.grib2\n",
       "58     watr      sfc  2015010100   c00.grib2       None\n",
       "59    weasd      sfc  2015010100   c00.grib2       None"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "variable_levels_df = pd.DataFrame(var_lev, columns=[\"variable\", \"level\", \"a\", \"b\", \"c\"])\n",
    "variable_levels_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1120ad21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['acpcp', 'apcp', 'cape', 'cin', 'dlwrf', 'dswrf', 'gflux', 'gust',\n",
       "       'hgt', 'hlcy', 'lhtfl', 'ncpcp', 'pbl', 'pres', 'pvort', 'pwat',\n",
       "       'rh', 'sfcr', 'shtfl', 'soilw', 'spfh', 'tcdc', 'tmax', 'tmin',\n",
       "       'tmp', 'tozne', 'tsoil', 'uflx', 'ugrd', 'ulwrf', 'uswrf', 'vflx',\n",
       "       'vgrd', 'vvel', 'watr', 'weasd'], dtype=object)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# These are the available variables\n",
    "variable_levels_df.variable.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "7ac88b17",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['sfc', 'ceiling', 'hybr', 'pres', 'hgt', 'msl', 'pvor', 'isen',\n",
       "       'eatm', 'bgrnd', '2m', 'tatm'], dtype=object)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# These are the available levels\n",
    "variable_levels_df.level.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "609535f0",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3.8.10 64-bit ('herbie': conda)",
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