python-awips/examples/notebooks/Model_Sounding_Data.ipynb

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    "<a name=\"top\"></a>\n",
    "<div style=\"width:1000 px\">\n",
    "\n",
    "<div style=\"float:right; width:98 px; height:98px;\">\n",
    "<img src=\"https://docs.unidata.ucar.edu/images/logos/unidata_logo_vertical_150x150.png\" alt=\"Unidata Logo\" style=\"height: 98px;\">\n",
    "</div>\n",
    "\n",
    "# Model Sounding Data\n",
    "**Python-AWIPS Tutorial Notebook**\n",
    "\n",
    "<div style=\"clear:both\"></div>\n",
    "</div>\n",
    "\n",
    "---\n",
    "\n",
    "<div style=\"float:right; width:250 px\"><img src=\"../images/model_sounding_preview.png\" alt=\"preview image of a model sounding skewt and hodograph\" style=\"height: 300px;\"></div>\n",
    "\n",
    "\n",
    "# Objectives\n",
    "\n",
    "* Use python-awips to connect to an edex server\n",
    "* Define and filter data request for model sounding data\n",
    "* Create vertical profiles from GFS BUFR products\n",
    "* Use MetPy to create [SkewT](https://unidata.github.io/MetPy/latest/api/generated/metpy.plots.SkewT.html) and [Hodograph](https://unidata.github.io/MetPy/latest/api/generated/metpy.plots.Hodograph.html) plots\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "toc": true
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   "source": [
    "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Imports\" data-toc-modified-id=\"Imports-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Imports</a></span></li><li><span><a href=\"#EDEX-Connection\" data-toc-modified-id=\"EDEX-Connection-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>EDEX Connection</a></span></li><li><span><a href=\"#Setting-Location\" data-toc-modified-id=\"Setting-Location-3\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>Setting Location</a></span><ul class=\"toc-item\"><li><span><a href=\"#Available-Location-Names\" data-toc-modified-id=\"Available-Location-Names-3.1\"><span class=\"toc-item-num\">3.1&nbsp;&nbsp;</span>Available Location Names</a></span></li><li><span><a href=\"#Setting-the-Location-Name\" data-toc-modified-id=\"Setting-the-Location-Name-3.2\"><span class=\"toc-item-num\">3.2&nbsp;&nbsp;</span>Setting the Location Name</a></span></li></ul></li><li><span><a href=\"#Filtering-by-Time\" data-toc-modified-id=\"Filtering-by-Time-4\"><span class=\"toc-item-num\">4&nbsp;&nbsp;</span>Filtering by Time</a></span></li><li><span><a href=\"#Get-the-Data!\" data-toc-modified-id=\"Get-the-Data!-5\"><span class=\"toc-item-num\">5&nbsp;&nbsp;</span>Get the Data!</a></span></li><li><span><a href=\"#Use-the-Data!\" data-toc-modified-id=\"Use-the-Data!-6\"><span class=\"toc-item-num\">6&nbsp;&nbsp;</span>Use the Data!</a></span><ul class=\"toc-item\"><li><span><a href=\"#Prepare-data-objects\" data-toc-modified-id=\"Prepare-data-objects-6.1\"><span class=\"toc-item-num\">6.1&nbsp;&nbsp;</span>Prepare data objects</a></span></li><li><span><a href=\"#Calculate-Dewpoint-from-Specific-Humidity\" data-toc-modified-id=\"Calculate-Dewpoint-from-Specific-Humidity-6.2\"><span class=\"toc-item-num\">6.2&nbsp;&nbsp;</span>Calculate Dewpoint from Specific Humidity</a></span><ul class=\"toc-item\"><li><span><a href=\"#Method-1\" data-toc-modified-id=\"Method-1-6.2.1\"><span class=\"toc-item-num\">6.2.1&nbsp;&nbsp;</span>Method 1</a></span></li><li><span><a href=\"#Method-2\" data-toc-modified-id=\"Method-2-6.2.2\"><span class=\"toc-item-num\">6.2.2&nbsp;&nbsp;</span>Method 2</a></span></li><li><span><a href=\"#Method-3\" data-toc-modified-id=\"Method-3-6.2.3\"><span class=\"toc-item-num\">6.2.3&nbsp;&nbsp;</span>Method 3</a></span></li></ul></li></ul></li><li><span><a href=\"#Plot-the-Data!\" data-toc-modified-id=\"Plot-the-Data!-7\"><span class=\"toc-item-num\">7&nbsp;&nbsp;</span>Plot the Data!</a></span></li><li><span><a href=\"#See-Also\" data-toc-modified-id=\"See-Also-8\"><span class=\"toc-item-num\">8&nbsp;&nbsp;</span>See Also</a></span><ul class=\"toc-item\"><li><span><a href=\"#Related-Notebooks\" data-toc-modified-id=\"Related-Notebooks-8.1\"><span class=\"toc-item-num\">8.1&nbsp;&nbsp;</span>Related Notebooks</a></span></li><li><span><a href=\"#Additional-Documentation\" data-toc-modified-id=\"Additional-Documentation-8.2\"><span class=\"toc-item-num\">8.2&nbsp;&nbsp;</span>Additional Documentation</a></span></li></ul></li></ul></div>"
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   "source": [
    "## Imports\n",
    "\n",
    "The imports below are used throughout the notebook.  Note the first import is coming directly from python-awips and allows us to connect to an EDEX server.  The subsequent imports are for data manipulation and visualization. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from awips.dataaccess import DataAccessLayer\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.axes_grid1.inset_locator import inset_axes\n",
    "from math import exp, log\n",
    "import numpy as np\n",
    "from metpy.calc import dewpoint, vapor_pressure, wind_speed, wind_direction\n",
    "from metpy.plots import SkewT, Hodograph\n",
    "from metpy.units import units"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## EDEX Connection\n",
    "\n",
    "First we establish a connection to Unidata's public EDEX server.  With that connection made, we can create a [new data request object](http://unidata.github.io/python-awips/api/IDataRequest.html) and set the data type to ***modelsounding***, and define additional parameters and an identifier on the request."
   ]
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   "source": [
    "DataAccessLayer.changeEDEXHost(\"edex-cloud.unidata.ucar.edu\")\n",
    "request = DataAccessLayer.newDataRequest(\"modelsounding\")\n",
    "forecastModel = \"GFS\"\n",
    "request.addIdentifier(\"reportType\", forecastModel)\n",
    "request.setParameters(\"pressure\",\"temperature\",\"specHum\",\"uComp\",\"vComp\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
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    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setting Location\n",
    "\n"
   ]
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   "source": [
    "### Available Location Names\n",
    "When working with a new data type, it is often useful to investigate all available options for a particular setting.  Shown below is how to see all available location names for a data request with type `modelsounding` and `reportType` identifier of `GFS`.  This step is not necessary if you already know exactly what the location name(s) you're interested in is."
   ]
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   "cell_type": "code",
   "execution_count": 3,
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       " 'KGFK',\n",
       " 'KGFL',\n",
       " 'KGGG',\n",
       " 'KGGW',\n",
       " 'KGJT',\n",
       " 'KGLD',\n",
       " 'KGLH',\n",
       " 'KGLS',\n",
       " 'KGMU',\n",
       " 'KGNR',\n",
       " 'KGNV',\n",
       " 'KGON',\n",
       " 'KGPT',\n",
       " 'KGRB',\n",
       " 'KGRI',\n",
       " 'KGRR',\n",
       " 'KGSO',\n",
       " 'KGSP',\n",
       " 'KGTF',\n",
       " 'KGUC',\n",
       " 'KGUP',\n",
       " 'KGWO',\n",
       " 'KGYY',\n",
       " 'KGZH',\n",
       " 'KHAT',\n",
       " 'KHBR',\n",
       " 'KHDN',\n",
       " 'KHIB',\n",
       " 'KHIO',\n",
       " 'KHKY',\n",
       " 'KHLG',\n",
       " 'KHLN',\n",
       " 'KHOB',\n",
       " 'KHON',\n",
       " 'KHOT',\n",
       " 'KHOU',\n",
       " 'KHPN',\n",
       " 'KHQM',\n",
       " 'KHRL',\n",
       " 'KHRO',\n",
       " 'KHSV',\n",
       " 'KHTH',\n",
       " 'KHTS',\n",
       " 'KHUF',\n",
       " 'KHUL',\n",
       " 'KHUT',\n",
       " 'KHVN',\n",
       " 'KHVR',\n",
       " 'KHYA',\n",
       " 'KIAD',\n",
       " 'KIAG',\n",
       " 'KIAH',\n",
       " 'KICT',\n",
       " 'KIDA',\n",
       " 'KIL',\n",
       " 'KILG',\n",
       " 'KILM',\n",
       " 'KIND',\n",
       " 'KINK',\n",
       " 'KINL',\n",
       " 'KINT',\n",
       " 'KINW',\n",
       " 'KIPL',\n",
       " 'KIPT',\n",
       " 'KISN',\n",
       " 'KISP',\n",
       " 'KITH',\n",
       " 'KIWD',\n",
       " 'KJAC',\n",
       " 'KJAN',\n",
       " 'KJAX',\n",
       " 'KJBR',\n",
       " 'KJFK',\n",
       " 'KJHW',\n",
       " 'KJKL',\n",
       " 'KJLN',\n",
       " 'KJMS',\n",
       " 'KJST',\n",
       " 'KJXN',\n",
       " 'KKL',\n",
       " 'KLAF',\n",
       " 'KLAN',\n",
       " 'KLAR',\n",
       " 'KLAS',\n",
       " 'KLAX',\n",
       " 'KLBB',\n",
       " 'KLBE',\n",
       " 'KLBF',\n",
       " 'KLCB',\n",
       " 'KLCH',\n",
       " 'KLEB',\n",
       " 'KLEX',\n",
       " 'KLFK',\n",
       " 'KLFT',\n",
       " 'KLGA',\n",
       " 'KLGB',\n",
       " 'KLGU',\n",
       " 'KLIT',\n",
       " 'KLMT',\n",
       " 'KLND',\n",
       " 'KLNK',\n",
       " 'KLOL',\n",
       " 'KLOZ',\n",
       " 'KLRD',\n",
       " 'KLSE',\n",
       " 'KLUK',\n",
       " 'KLVS',\n",
       " 'KLWB',\n",
       " 'KLWM',\n",
       " 'KLWS',\n",
       " 'KLWT',\n",
       " 'KLYH',\n",
       " 'KLZK',\n",
       " 'KMAF',\n",
       " 'KMBS',\n",
       " 'KMCB',\n",
       " 'KMCE',\n",
       " 'KMCI',\n",
       " 'KMCN',\n",
       " 'KMCO',\n",
       " 'KMCW',\n",
       " 'KMDN',\n",
       " 'KMDT',\n",
       " 'KMDW',\n",
       " 'KMEI',\n",
       " 'KMEM',\n",
       " 'KMFD',\n",
       " 'KMFE',\n",
       " 'KMFR',\n",
       " 'KMGM',\n",
       " 'KMGW',\n",
       " 'KMHE',\n",
       " 'KMHK',\n",
       " 'KMHT',\n",
       " 'KMHX',\n",
       " 'KMIA',\n",
       " 'KMIV',\n",
       " 'KMKC',\n",
       " 'KMKE',\n",
       " 'KMKG',\n",
       " 'KMKL',\n",
       " 'KMLB',\n",
       " 'KMLC',\n",
       " 'KMLI',\n",
       " 'KMLS',\n",
       " 'KMLT',\n",
       " 'KMLU',\n",
       " 'KMMU',\n",
       " 'KMOB',\n",
       " 'KMOT',\n",
       " 'KMPV',\n",
       " 'KMQT',\n",
       " 'KMRB',\n",
       " 'KMRY',\n",
       " 'KMSL',\n",
       " 'KMSN',\n",
       " 'KMSO',\n",
       " 'KMSP',\n",
       " 'KMSS',\n",
       " 'KMSY',\n",
       " 'KMTJ',\n",
       " 'KMTN',\n",
       " 'KMWH',\n",
       " 'KMYR',\n",
       " 'KNA',\n",
       " 'KNEW',\n",
       " 'KNL',\n",
       " 'KNSI',\n",
       " 'KOAK',\n",
       " 'KOFK',\n",
       " 'KOGD',\n",
       " 'KOKC',\n",
       " 'KOLM',\n",
       " 'KOMA',\n",
       " 'KONT',\n",
       " 'KOPF',\n",
       " 'KOQU',\n",
       " 'KORD',\n",
       " 'KORF',\n",
       " 'KORH',\n",
       " 'KOSH',\n",
       " 'KOTH',\n",
       " 'KOTM',\n",
       " 'KP11',\n",
       " 'KP38',\n",
       " 'KPAE',\n",
       " 'KPAH',\n",
       " 'KPBF',\n",
       " 'KPBI',\n",
       " 'KPDK',\n",
       " 'KPDT',\n",
       " 'KPDX',\n",
       " 'KPFN',\n",
       " 'KPGA',\n",
       " 'KPHF',\n",
       " 'KPHL',\n",
       " 'KPHN',\n",
       " 'KPHX',\n",
       " 'KPIA',\n",
       " 'KPIB',\n",
       " 'KPIE',\n",
       " 'KPIH',\n",
       " 'KPIR',\n",
       " 'KPIT',\n",
       " 'KPKB',\n",
       " 'KPLN',\n",
       " 'KPMD',\n",
       " 'KPNC',\n",
       " 'KPNE',\n",
       " 'KPNS',\n",
       " 'KPOU',\n",
       " 'KPQI',\n",
       " 'KPRB',\n",
       " 'KPRC',\n",
       " 'KPSC',\n",
       " 'KPSM',\n",
       " 'KPSP',\n",
       " 'KPTK',\n",
       " 'KPUB',\n",
       " 'KPVD',\n",
       " 'KPVU',\n",
       " 'KPWM',\n",
       " 'KRAD',\n",
       " 'KRAP',\n",
       " 'KRBL',\n",
       " 'KRDD',\n",
       " 'KRDG',\n",
       " 'KRDM',\n",
       " 'KRDU',\n",
       " 'KRFD',\n",
       " 'KRIC',\n",
       " 'KRIW',\n",
       " 'KRKD',\n",
       " 'KRKS',\n",
       " 'KRNO',\n",
       " 'KRNT',\n",
       " 'KROA',\n",
       " 'KROC',\n",
       " 'KROW',\n",
       " 'KRSL',\n",
       " 'KRST',\n",
       " 'KRSW',\n",
       " 'KRUM',\n",
       " 'KRWF',\n",
       " 'KRWI',\n",
       " 'KRWL',\n",
       " 'KSAC',\n",
       " 'KSAF',\n",
       " 'KSAN',\n",
       " 'KSAT',\n",
       " 'KSAV',\n",
       " 'KSBA',\n",
       " 'KSBN',\n",
       " 'KSBP',\n",
       " 'KSBY',\n",
       " 'KSCH',\n",
       " 'KSCK',\n",
       " 'KSDF',\n",
       " 'KSDM',\n",
       " 'KSDY',\n",
       " 'KSEA',\n",
       " 'KSEP',\n",
       " 'KSFF',\n",
       " 'KSFO',\n",
       " 'KSGF',\n",
       " 'KSGU',\n",
       " 'KSHR',\n",
       " 'KSHV',\n",
       " 'KSJC',\n",
       " 'KSJT',\n",
       " 'KSLC',\n",
       " 'KSLE',\n",
       " 'KSLK',\n",
       " 'KSLN',\n",
       " 'KSMF',\n",
       " 'KSMX',\n",
       " 'KSNA',\n",
       " 'KSNS',\n",
       " 'KSPI',\n",
       " 'KSPS',\n",
       " 'KSRQ',\n",
       " 'KSSI',\n",
       " 'KSTJ',\n",
       " 'KSTL',\n",
       " 'KSTP',\n",
       " 'KSTS',\n",
       " 'KSUN',\n",
       " 'KSUS',\n",
       " 'KSUX',\n",
       " 'KSVE',\n",
       " 'KSWF',\n",
       " 'KSYR',\n",
       " 'KTCC',\n",
       " 'KTCL',\n",
       " 'KTCS',\n",
       " 'KTEB',\n",
       " 'KTIW',\n",
       " 'KTLH',\n",
       " 'KTMB',\n",
       " 'KTOL',\n",
       " 'KTOP',\n",
       " 'KTPA',\n",
       " 'KTPH',\n",
       " 'KTRI',\n",
       " 'KTRK',\n",
       " 'KTRM',\n",
       " 'KTTD',\n",
       " 'KTTN',\n",
       " 'KTUL',\n",
       " 'KTUP',\n",
       " 'KTUS',\n",
       " 'KTVC',\n",
       " 'KTVL',\n",
       " 'KTWF',\n",
       " 'KTXK',\n",
       " 'KTYR',\n",
       " 'KTYS',\n",
       " 'KUCA',\n",
       " 'KUIN',\n",
       " 'KUKI',\n",
       " 'KUNV',\n",
       " 'KVCT',\n",
       " 'KVEL',\n",
       " 'KVLD',\n",
       " 'KVNY',\n",
       " 'KVRB',\n",
       " 'KWJF',\n",
       " 'KWMC',\n",
       " 'KWRL',\n",
       " 'KWYS',\n",
       " 'KY22',\n",
       " 'KY26',\n",
       " 'KYKM',\n",
       " 'KYKN',\n",
       " 'KYNG',\n",
       " 'KYUM',\n",
       " 'KZZV',\n",
       " 'LAA',\n",
       " 'LAP',\n",
       " 'LBY',\n",
       " 'LDL',\n",
       " 'LHX',\n",
       " 'LIC',\n",
       " 'LOR',\n",
       " 'LRR',\n",
       " 'LSF',\n",
       " 'LUS',\n",
       " 'LVM',\n",
       " 'LW1',\n",
       " 'MAC',\n",
       " 'MAX',\n",
       " 'MAZ',\n",
       " 'MDPC',\n",
       " 'MDPP',\n",
       " 'MDSD',\n",
       " 'MDST',\n",
       " 'MGFL',\n",
       " 'MGGT',\n",
       " 'MGHT',\n",
       " 'MGPB',\n",
       " 'MGSJ',\n",
       " 'MHAM',\n",
       " 'MHCA',\n",
       " 'MHCH',\n",
       " 'MHLC',\n",
       " 'MHLE',\n",
       " 'MHLM',\n",
       " 'MHNJ',\n",
       " 'MHPL',\n",
       " 'MHRO',\n",
       " 'MHSR',\n",
       " 'MHTE',\n",
       " 'MHTG',\n",
       " 'MHYR',\n",
       " 'MIB',\n",
       " 'MIE',\n",
       " 'MKJP',\n",
       " 'MKJS',\n",
       " 'MLD',\n",
       " 'MMAA',\n",
       " 'MMAS',\n",
       " 'MMBT',\n",
       " 'MMCE',\n",
       " 'MMCL',\n",
       " 'MMCN',\n",
       " 'MMCS',\n",
       " 'MMCU',\n",
       " 'MMCV',\n",
       " 'MMCZ',\n",
       " 'MMDO',\n",
       " 'MMGL',\n",
       " 'MMGM',\n",
       " 'MMHO',\n",
       " 'MMLP',\n",
       " 'MMMA',\n",
       " 'MMMD',\n",
       " 'MMML',\n",
       " 'MMMM',\n",
       " 'MMMT',\n",
       " 'MMMX',\n",
       " 'MMMY',\n",
       " 'MMMZ',\n",
       " 'MMNL',\n",
       " 'MMPR',\n",
       " 'MMRX',\n",
       " 'MMSD',\n",
       " 'MMSP',\n",
       " 'MMTC',\n",
       " 'MMTJ',\n",
       " 'MMTM',\n",
       " 'MMTO',\n",
       " 'MMTP',\n",
       " 'MMUN',\n",
       " 'MMVR',\n",
       " 'MMZC',\n",
       " 'MMZH',\n",
       " 'MMZO',\n",
       " 'MNMG',\n",
       " 'MNPC',\n",
       " 'MOR',\n",
       " 'MPBO',\n",
       " 'MPCH',\n",
       " 'MPDA',\n",
       " 'MPMG',\n",
       " 'MPSA',\n",
       " 'MPTO',\n",
       " 'MPX',\n",
       " 'MRCH',\n",
       " 'MRF',\n",
       " 'MRLB',\n",
       " 'MRLM',\n",
       " 'MROC',\n",
       " 'MRPV',\n",
       " 'MRS',\n",
       " 'MSAC',\n",
       " 'MSLP',\n",
       " 'MSSS',\n",
       " 'MTCH',\n",
       " 'MTL',\n",
       " 'MTPP',\n",
       " 'MTV',\n",
       " 'MTY',\n",
       " 'MUBA',\n",
       " 'MUBY',\n",
       " 'MUCA',\n",
       " 'MUCL',\n",
       " 'MUCM',\n",
       " 'MUCU',\n",
       " 'MUGM',\n",
       " 'MUGT',\n",
       " 'MUHA',\n",
       " 'MUMO',\n",
       " 'MUMZ',\n",
       " 'MUNG',\n",
       " 'MUVR',\n",
       " 'MUVT',\n",
       " 'MWCR',\n",
       " 'MYBS',\n",
       " 'MYEG',\n",
       " 'MYGF',\n",
       " 'MYGW',\n",
       " 'MYL',\n",
       " 'MYNN',\n",
       " 'MZBZ',\n",
       " 'MZT',\n",
       " 'NCK',\n",
       " 'NGX',\n",
       " 'NHK',\n",
       " 'NID',\n",
       " 'NKX',\n",
       " 'NOA',\n",
       " 'NRU',\n",
       " 'NTD',\n",
       " ...]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "locations = DataAccessLayer.getAvailableLocationNames(request)\n",
    "locations.sort()\n",
    "list(locations)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Setting the Location Name\n",
    "\n",
    "In this case we're setting the location name to `KFRM` which is the Municipal Airport in Fairmont, Minnesota."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "request.setLocationNames(\"KFRM\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filtering by Time\n",
    "\n",
    "Models produce many different time variants during their runs, so let's limit the data to the most recent time and forecast run."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "cycles = DataAccessLayer.getAvailableTimes(request, True)\n",
    "times = DataAccessLayer.getAvailableTimes(request)\n",
    "\n",
    "try:\n",
    "    fcstRun = DataAccessLayer.getForecastRun(cycles[-1], times)\n",
    "    list(fcstRun)\n",
    "    response = DataAccessLayer.getGeometryData(request,[fcstRun[0]])\n",
    "except:\n",
    "    print('No times available')\n",
    "    exit"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get the Data!\n",
    "\n",
    "Here we can now request our data response from the EDEX server with our defined time filter.\n",
    "Printing out some data about the response verifies we received the data we were interested in."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "parms    = ['temperature', 'pressure', 'vComp', 'uComp', 'specHum']\n",
      "site     = KFRM\n",
      "geom     = POINT (-94.41999816894531 43.65000152587891)\n",
      "datetime = 2022-08-19 12:00:00\n",
      "reftime  = Aug 19 22 12:00:00 GMT\n",
      "fcstHour = 0\n",
      "period   = (Aug 19 22 12:00:00 , Aug 19 22 12:00:00 )\n"
     ]
    }
   ],
   "source": [
    "obj = response[0]\n",
    "\n",
    "print(\"parms    = \" + str(obj.getParameters()))\n",
    "print(\"site     = \" + str(obj.getLocationName()))\n",
    "print(\"geom     = \" + str(obj.getGeometry()))\n",
    "print(\"datetime = \" + str(obj.getDataTime()))\n",
    "print(\"reftime  = \" + str(obj.getDataTime().getRefTime()))\n",
    "print(\"fcstHour = \" + str(obj.getDataTime().getFcstTime()))\n",
    "print(\"period   = \" + str(obj.getDataTime().getValidPeriod()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Use the Data!\n",
    "\n",
    "Since we filtered on time, and requested the data in the previous cell, we now have a `response` object we can work with."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prepare data objects\n",
    "\n",
    "Here we construct arrays for each parameter to plot (temperature, pressure, moisture (spec. humidity), wind components, and cloud cover).  We have two sets of arrays for temperature and pressure, where the second set only has values as long as the specific humidity is not zero.  That is because we are going to do some calculations with specific humidity, temperature, and pressure and we need all those arrays to be the same length, and for the specific humidty to not equal zero."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create new arrays to populate from our response objects\n",
    "tmp,prs,sh,prs2,tmp2 = np.array([]),np.array([]),np.array([]),np.array([]),np.array([])\n",
    "uc,vc = np.array([]),np.array([])\n",
    "\n",
    "# Cycle through all response objects to populate new arrays\n",
    "for ob in response:\n",
    "    tmp = np.append(tmp,ob.getNumber(\"temperature\"))\n",
    "    prs = np.append(prs,ob.getNumber(\"pressure\"))\n",
    "    uc = np.append(uc,ob.getNumber(\"uComp\"))\n",
    "    vc = np.append(vc,ob.getNumber(\"vComp\"))\n",
    "    # don't include data with 0 specific humidity\n",
    "    if(ob.getNumber(\"specHum\")==0):\n",
    "        continue\n",
    "    sh = np.append(sh,ob.getNumber(\"specHum\"))\n",
    "    prs2 = np.append(prs2,ob.getNumber(\"pressure\"))\n",
    "    tmp2 = np.append(tmp2,ob.getNumber(\"temperature\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculate Dewpoint from Specific Humidity\n",
    "\n",
    "Because the modelsounding plugin does not return dewpoint values, we must calculate the profile ourselves.  Here are three examples of dewpoint calculated from specific humidity, including a manual calculation following NCEP AWIPS/NSHARP. \n",
    "\n",
    "First, we'll set up variables that are used in all three methods (and later in the notebook)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "tfull = (tmp-273.15) * units.degC\n",
    "t = (tmp2-273.15) * units.degC\n",
    "\n",
    "pfull = prs/100 * units.mbar\n",
    "p = prs2/100 * units.mbar\n",
    "\n",
    "u,v = uc*1.94384,vc*1.94384 # m/s to knots\n",
    "spd = wind_speed(u*units.knots, v*units.knots)\n",
    "dir = wind_direction(u*units.knots, v*units.knots) * units.deg"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Method 1\n",
    "\n",
    "Here we'll calculate the dewpoint using MetPy calculated mixing ratio and the vapor pressure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "rmix = (sh/(1-sh)) *1000 * units('g/kg')\n",
    "e = vapor_pressure(p, rmix)\n",
    "td = dewpoint(e)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Method 2\n",
    "\n",
    "Here we'll calculate dewpoint using MetPy while assuming the mixing ratio is equal to the specific humidity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "td2 = dewpoint(vapor_pressure(p, sh))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Method 3\n",
    "\n",
    "Here we use logic from the NCEP AWIPS soundingrequest plugin.  This logic was based on [GEMPAK and NSHARP calculations](https://github.com/Unidata/awips2-ncep/blob/unidata_16.2.2/edex/gov.noaa.nws.ncep.edex.plugin.soundingrequest/src/gov/noaa/nws/ncep/edex/plugin/soundingrequest/handler/MergeSounding.java#L1783)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# new arrays\n",
    "ntmp = tmp2\n",
    "\n",
    "# where p=pressure(pa), T=temp(C), T0=reference temp(273.16)\n",
    "rh = 0.263*prs2*sh / (np.exp(17.67*ntmp/(ntmp+273.15-29.65)))\n",
    "vaps =  6.112 * np.exp((17.67 * ntmp) / (ntmp + 243.5))\n",
    "vapr = rh * vaps / 100\n",
    "dwpc = np.array(243.5 * (np.log(6.112) - np.log(vapr)) / (np.log(vapr) - np.log(6.112) - 17.67)) * units.degC"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot the Data!\n",
    "\n",
    "Create and display SkewT and Hodograph plots using MetPy.\n",
    "\n",
    "Since we're displaying all three dewpoint plots, we also create a \"zoomed in\" view to highlight the slight differences between the three calculations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x1008 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a new figure and define the size\n",
    "fig = plt.figure(figsize=(12, 14))\n",
    "\n",
    "# Create a skewT plot\n",
    "skew = SkewT(fig)\n",
    "\n",
    "# Plot the data\n",
    "skew.plot(pfull, tfull, 'r', linewidth=2)\n",
    "skew.plot(p, td, 'b', linewidth=2)\n",
    "skew.plot(p, td2, 'y', linewidth=2)\n",
    "skew.plot(p, dwpc, 'g', linewidth=2)\n",
    "skew.plot_barbs(pfull, u, v)\n",
    "# set the domain and range (these may need to be adjusted\n",
    "# depending on the exact data for best viewing purposes)\n",
    "skew.ax.set_ylim(1000, 100)\n",
    "skew.ax.set_xlim(-70, 40)\n",
    "\n",
    "# Add title to the plot\n",
    "# format: \"2022-08-18 18Z FH 0  | GFS KFRM (43.65,-94.42)\"\n",
    "datetime = str(ob.getDataTime())[0:-6]+\"Z\"\n",
    "forecastHr = str(ob.getDataTime().getFcstTime())\n",
    "site = ob.getLocationName()\n",
    "lat = \"{:.2f}\".format(ob.getGeometry().y)\n",
    "lon = \"{:.2f}\".format(ob.getGeometry().x)\n",
    "coords = \"(\" + lat + \", \" + lon +\")\"\n",
    "\n",
    "title = datetime + \" FH \" + forecastHr + \" | \" + forecastModel + \" \" + site + \" \" + coords\n",
    "plt.title(title)\n",
    "\n",
    "# Create a secondary axes for the \"zoomed in\" view\n",
    "zoom_ax = inset_axes(skew.ax, '35%', '35%', loc=3,\n",
    "                     bbox_to_anchor=(.05, .05, 1, 1),\n",
    "                     bbox_transform=skew.ax.transAxes)\n",
    "# create a secondary plot for zoomed in section\n",
    "fig2 = plt.figure()\n",
    "skew2 = SkewT(fig2)\n",
    "skew2.ax = zoom_ax\n",
    "skew2.plot(p, td, 'b', linewidth=2, label='MetPy calculated mixing ratio')\n",
    "skew2.plot(p, td2, 'y', linewidth=2, label='MetPy spec. hum = mixing ratio')\n",
    "skew2.plot(p, dwpc, 'g', linewidth=2, label='GEMPAK legacy caluclation')\n",
    "# create a legend to explain the three lines\n",
    "skew2.ax.legend(loc=1)\n",
    "# remove the axis title on the zoomed plot since they\n",
    "# are redundant and just clutter the plot\n",
    "skew2.ax.set_xlabel(\"\")\n",
    "skew2.ax.set_ylabel(\"\")\n",
    "# these exact bounds may need to change depending on\n",
    "# the most recent data\n",
    "skew2.ax.set_ylim(970, 900)\n",
    "skew2.ax.set_xlim(11, 14)\n",
    "\n",
    "# draw an indicator in the main plot of the \"zoomed in\" region\n",
    "skew.ax.indicate_inset_zoom(zoom_ax, edgecolor=\"black\")\n",
    "\n",
    "# dispose of the second figure, since creating a new\n",
    "# skewt in metpy automatically creates a new figure\n",
    "# which is unnecessary in this case\n",
    "plt.close(fig2)\n",
    "\n",
    "# An example of a slanted line at constant T -- in this case the 0 isotherm\n",
    "l = skew.ax.axvline(0, color='c', linestyle='--', linewidth=2)\n",
    "\n",
    "# Draw hodograph\n",
    "ax_hod = inset_axes(skew.ax, '40%', '40%', loc=1)\n",
    "h = Hodograph(ax_hod, component_range=spd.max()/units.knots)\n",
    "h.add_grid(increment=20)\n",
    "h.plot_colormapped(u, v, spd)\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## See Also\n",
    "\n",
    "### Related Notebooks\n",
    "\n",
    "* [Grid Levels and Parameters](https://unidata.github.io/python-awips/examples/generated/Grid_Levels_and_Parameters.html)\n",
    "* [Upper Air BUFR Soundings](http://unidata.github.io/python-awips/examples/generated/Upper_Air_BUFR_Soundings.html)\n",
    "* [Forecast Model Vertical Sounding](http://unidata.github.io/python-awips/examples/generated/Forecast_Model_Vertical_Sounding.html)\n",
    "\n",
    "### Additional Documentation\n",
    "\n",
    "**python-awips:**\n",
    "* [awips.DataAccessLayer](http://unidata.github.io/python-awips/api/DataAccessLayer.html)\n",
    "* [awips.PyGeometryData](http://unidata.github.io/python-awips/api/PyGeometryData.html)\n",
    "\n",
    "**matplotlib:**\n",
    "* [matplotlib.pyplot](https://matplotlib.org/3.3.3/api/_as_gen/matplotlib.pyplot.html)\n",
    "* [metpy.skewt](https://unidata.github.io/MetPy/latest/api/generated/metpy.plots.SkewT.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"#top\">Top</a>\n",
    "\n",
    "---"
   ]
  }
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