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 identifer on the request."
   ]
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   "cell_type": "code",
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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": {},
   "source": [
    "<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 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 = 2022-08-18 18:00:00\n",
      "reftime  = Aug 18 22 18:00:00 GMT\n",
      "fcstHour = 0\n",
      "period   = (Aug 18 22 18:00:00 , Aug 18 22 18:00:00 )\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 a title to the plot\n",
    "plt.title( forecastModel + \" \" \\\n",
    "          + ob.getLocationName() \\\n",
    "          + \"(\"+ str(ob.getGeometry()) + \")\" \\\n",
    "          + \", \" + str(ob.getDataTime()))\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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