python-awips/examples/notebooks/Model_Sounding_Data.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Python-AWIPS Tutorial Notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\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": {},
   "source": [
    "## Table of Contents\n",
    "\n",
    "[1 Imports](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html#imports)<br>  \n",
    "[2 EDEX Connection](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html#edex-connection)<br>  \n",
    "[3 Setting Location](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html#setting-location)<br>  \n",
    "&nbsp;&nbsp;&nbsp;&nbsp;[3.1 Available Location Names](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html#available-location-names)<br>  \n",
    "&nbsp;&nbsp;&nbsp;&nbsp;[3.2 Setting the Location Name](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html#setting-the-location-name)<br>  \n",
    "[4 Filtering by Time](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html#filtering-by-time)<br>  \n",
    "[5 Get the Data!](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html#get-the-data)<br>  \n",
    "[6 Use the Data!](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html#use-the-data)<br>  \n",
    "&nbsp;&nbsp;&nbsp;&nbsp;[6.1 Prepare the Data!](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html#prepare-the-data)<br>  \n",
    "&nbsp;&nbsp;&nbsp;&nbsp;[6.2 Calculate Dewpoint from Specific Humidity](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html#calculate-dewpoint-from-specific-humidity)<br>  \n",
    "&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[6.2.1 Method 1](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html#method-1)<br>  \n",
    "&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[6.2.2 Method 2](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html#method-2)<br>  \n",
    "&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[6.2.3 Method 3](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html#method-3)<br>  \n",
    "[7 Plot the Data!](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html#plot-the-data)<br>  \n",
    "[8 See Also](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html#see-also)<br>  \n",
    "&nbsp;&nbsp;&nbsp;&nbsp;[8.1 Related Notebooks](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html#related-notebooks)<br>  \n",
    "&nbsp;&nbsp;&nbsp;&nbsp;[8.2 Additional Documentation](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html#additional-documentation)<br>  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1 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": {
    "scrolled": true
   },
   "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": [
    "[Top](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html)\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2 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."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "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": [
    "[Top](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html)\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3 Setting Location"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1 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."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['',\n",
       " '1V4',\n",
       " '3J2',\n",
       " '4BL',\n",
       " '4BQ',\n",
       " '4HV',\n",
       " '4OM',\n",
       " '5AF',\n",
       " '5AG',\n",
       " '5SZ',\n",
       " '6RO',\n",
       " '8V7',\n",
       " '9B6',\n",
       " 'A#2',\n",
       " 'A#3',\n",
       " 'A#4',\n",
       " 'A#5',\n",
       " 'A#6',\n",
       " 'A#7',\n",
       " 'A#8',\n",
       " 'A#9',\n",
       " 'A#A',\n",
       " 'A#B',\n",
       " 'ABL',\n",
       " 'ADM',\n",
       " 'AFA',\n",
       " 'AGR',\n",
       " 'AHN',\n",
       " 'AIA',\n",
       " 'AIH',\n",
       " 'AJO',\n",
       " 'ANJ',\n",
       " 'APX',\n",
       " 'AQQ',\n",
       " 'ATH',\n",
       " 'ATL1',\n",
       " 'ATL2',\n",
       " 'ATL3',\n",
       " 'ATL4',\n",
       " 'ATLH',\n",
       " 'AWH',\n",
       " 'AWR',\n",
       " 'B#1',\n",
       " 'B#2',\n",
       " 'B#3',\n",
       " 'B#4',\n",
       " 'B#5',\n",
       " 'B#6',\n",
       " 'B#7',\n",
       " 'B#8',\n",
       " 'B#9',\n",
       " 'B#A',\n",
       " 'B#B',\n",
       " 'B#C',\n",
       " 'B#D',\n",
       " 'B#E',\n",
       " 'B#F',\n",
       " 'B#G',\n",
       " 'B#H',\n",
       " 'B#J',\n",
       " 'B#K',\n",
       " 'B#L',\n",
       " 'B#M',\n",
       " 'B#N',\n",
       " 'B#O',\n",
       " 'B#P',\n",
       " 'B#Q',\n",
       " 'B#S',\n",
       " 'BAB',\n",
       " 'BDG',\n",
       " 'BDP',\n",
       " 'BFL',\n",
       " 'BGTL',\n",
       " 'BH1',\n",
       " 'BH2',\n",
       " 'BH3',\n",
       " 'BH4',\n",
       " 'BH5',\n",
       " 'BHK',\n",
       " 'BID',\n",
       " 'BIR',\n",
       " 'BLS',\n",
       " 'BLU',\n",
       " 'BMX',\n",
       " 'BNA',\n",
       " 'BOD',\n",
       " 'BRA',\n",
       " 'BTL',\n",
       " 'BVR',\n",
       " 'C01',\n",
       " 'C02',\n",
       " 'C03',\n",
       " 'C04',\n",
       " 'C06',\n",
       " 'C07',\n",
       " 'C08',\n",
       " 'C09',\n",
       " 'C10',\n",
       " 'C11',\n",
       " 'C12',\n",
       " 'C13',\n",
       " 'C14',\n",
       " 'C17',\n",
       " 'C18',\n",
       " 'C19',\n",
       " 'C20',\n",
       " 'C21',\n",
       " 'C22',\n",
       " 'C23',\n",
       " 'C24',\n",
       " 'C25',\n",
       " 'C27',\n",
       " 'C28',\n",
       " 'C30',\n",
       " 'C31',\n",
       " 'C32',\n",
       " 'C33',\n",
       " 'C34',\n",
       " 'C35',\n",
       " 'C36',\n",
       " 'C7H',\n",
       " 'CAI',\n",
       " 'CAN',\n",
       " 'CBE',\n",
       " 'CBN',\n",
       " 'CHE',\n",
       " 'CKN',\n",
       " 'CLD',\n",
       " 'CLE',\n",
       " 'CLN',\n",
       " 'COL1',\n",
       " 'COL2',\n",
       " 'COL3',\n",
       " 'COL4',\n",
       " 'COT',\n",
       " 'CQV',\n",
       " 'CRL',\n",
       " 'CRR',\n",
       " 'CTY',\n",
       " 'CVM',\n",
       " 'CVS',\n",
       " 'CWEU',\n",
       " 'CWFN',\n",
       " 'CWKX',\n",
       " 'CWLB',\n",
       " 'CWLO',\n",
       " 'CWLT',\n",
       " 'CWLW',\n",
       " 'CWMW',\n",
       " 'CWOS',\n",
       " 'CWPH',\n",
       " 'CWQG',\n",
       " 'CWSA',\n",
       " 'CWSE',\n",
       " 'CWZB',\n",
       " 'CWZC',\n",
       " 'CWZV',\n",
       " 'CYAH',\n",
       " 'CYAW',\n",
       " 'CYBK',\n",
       " 'CYBU',\n",
       " 'CYCB',\n",
       " 'CYCG',\n",
       " 'CYCX',\n",
       " 'CYDA',\n",
       " 'CYEG',\n",
       " 'CYEV',\n",
       " 'CYFB',\n",
       " 'CYFO',\n",
       " 'CYFS',\n",
       " 'CYGQ',\n",
       " 'CYHM',\n",
       " 'CYHZ',\n",
       " 'CYJT',\n",
       " 'CYLH',\n",
       " 'CYLJ',\n",
       " 'CYMD',\n",
       " 'CYMO',\n",
       " 'CYMT',\n",
       " 'CYMX',\n",
       " 'CYOC',\n",
       " 'CYOW',\n",
       " 'CYPA',\n",
       " 'CYPE',\n",
       " 'CYPL',\n",
       " 'CYPQ',\n",
       " 'CYQA',\n",
       " 'CYQD',\n",
       " 'CYQG',\n",
       " 'CYQH',\n",
       " 'CYQI',\n",
       " 'CYQK',\n",
       " 'CYQQ',\n",
       " 'CYQR',\n",
       " 'CYQT',\n",
       " 'CYQX',\n",
       " 'CYQY',\n",
       " 'CYRB',\n",
       " 'CYSM',\n",
       " 'CYSY',\n",
       " 'CYTH',\n",
       " 'CYTL',\n",
       " 'CYTS',\n",
       " 'CYUL',\n",
       " 'CYUX',\n",
       " 'CYVO',\n",
       " 'CYVP',\n",
       " 'CYVQ',\n",
       " 'CYVR',\n",
       " 'CYVV',\n",
       " 'CYWA',\n",
       " 'CYWG',\n",
       " 'CYWO',\n",
       " 'CYXC',\n",
       " 'CYXE',\n",
       " 'CYXH',\n",
       " 'CYXS',\n",
       " 'CYXU',\n",
       " 'CYXX',\n",
       " 'CYXY',\n",
       " 'CYXZ',\n",
       " 'CYYB',\n",
       " 'CYYC',\n",
       " 'CYYE',\n",
       " 'CYYJ',\n",
       " 'CYYQ',\n",
       " 'CYYR',\n",
       " 'CYYT',\n",
       " 'CYYZ',\n",
       " 'CYZF',\n",
       " 'CYZS',\n",
       " 'CYZT',\n",
       " 'CYZV',\n",
       " 'DEN',\n",
       " 'DOV',\n",
       " 'DPG',\n",
       " 'DSC',\n",
       " 'DSD',\n",
       " 'DTX',\n",
       " 'DVN',\n",
       " 'DYS',\n",
       " 'E28',\n",
       " 'E74',\n",
       " 'EAT',\n",
       " 'EAX',\n",
       " 'EDW',\n",
       " 'EFL',\n",
       " 'EMP',\n",
       " 'END',\n",
       " 'ENL',\n",
       " 'ESTC',\n",
       " 'FCS',\n",
       " 'FDR',\n",
       " 'FFC',\n",
       " 'FHU',\n",
       " 'FLG',\n",
       " 'FLP',\n",
       " 'FPK',\n",
       " 'FRI',\n",
       " 'FSI',\n",
       " 'FTR',\n",
       " 'FWD',\n",
       " 'G#1',\n",
       " 'G#2',\n",
       " 'G#3',\n",
       " 'G#4',\n",
       " 'G#5',\n",
       " 'G#6',\n",
       " 'G#7',\n",
       " 'G#8',\n",
       " 'G#9',\n",
       " 'G#A',\n",
       " 'G#B',\n",
       " 'G#C',\n",
       " 'G#D',\n",
       " 'G#E',\n",
       " 'G#F',\n",
       " 'G#G',\n",
       " 'G001',\n",
       " 'G003',\n",
       " 'G004',\n",
       " 'G005',\n",
       " 'G007',\n",
       " 'G009',\n",
       " 'GDP',\n",
       " 'GDV',\n",
       " 'GLRY',\n",
       " 'GMX1',\n",
       " 'GNB',\n",
       " 'GNC',\n",
       " 'GRF',\n",
       " 'GTB',\n",
       " 'GTP',\n",
       " 'GVL',\n",
       " 'GVS',\n",
       " 'GYX',\n",
       " 'H02',\n",
       " 'HAY',\n",
       " 'HGR',\n",
       " 'HMN',\n",
       " 'HOM',\n",
       " 'HOO',\n",
       " 'HSI',\n",
       " 'HYR',\n",
       " 'HYS',\n",
       " 'ICC',\n",
       " 'IGM',\n",
       " 'ILN',\n",
       " 'ILS',\n",
       " 'ILX',\n",
       " 'IMT',\n",
       " 'INK',\n",
       " 'IPX',\n",
       " 'JACK',\n",
       " 'JDN',\n",
       " 'K40B',\n",
       " 'K9V9',\n",
       " 'KABE',\n",
       " 'KABI',\n",
       " 'KABQ',\n",
       " 'KABR',\n",
       " 'KABY',\n",
       " 'KACK',\n",
       " 'KACT',\n",
       " 'KACV',\n",
       " 'KACY',\n",
       " 'KAGC',\n",
       " 'KAGS',\n",
       " 'KAHN',\n",
       " 'KAK',\n",
       " 'KALB',\n",
       " 'KALI',\n",
       " 'KALO',\n",
       " 'KALS',\n",
       " 'KALW',\n",
       " 'KAMA',\n",
       " 'KAN',\n",
       " 'KANB',\n",
       " 'KAND',\n",
       " 'KAOO',\n",
       " 'KAPA',\n",
       " 'KAPN',\n",
       " 'KART',\n",
       " 'KASE',\n",
       " 'KAST',\n",
       " 'KATL',\n",
       " 'KATY',\n",
       " 'KAUG',\n",
       " 'KAUS',\n",
       " 'KAUW',\n",
       " 'KAVL',\n",
       " 'KAVP',\n",
       " 'KAXN',\n",
       " 'KAYS',\n",
       " 'KAZO',\n",
       " 'KBAF',\n",
       " 'KBCE',\n",
       " 'KBDE',\n",
       " 'KBDL',\n",
       " 'KBDR',\n",
       " 'KBED',\n",
       " 'KBFD',\n",
       " 'KBFF',\n",
       " 'KBFI',\n",
       " 'KBFL',\n",
       " 'KBGM',\n",
       " 'KBGR',\n",
       " 'KBHB',\n",
       " 'KBHM',\n",
       " 'KBIH',\n",
       " 'KBIL',\n",
       " 'KBIS',\n",
       " 'KBJC',\n",
       " 'KBJI',\n",
       " 'KBKE',\n",
       " 'KBKW',\n",
       " 'KBLF',\n",
       " 'KBLH',\n",
       " 'KBLI',\n",
       " 'KBML',\n",
       " 'KBNA',\n",
       " 'KBNO',\n",
       " 'KBNV',\n",
       " 'KBOI',\n",
       " 'KBOS',\n",
       " 'KBPT',\n",
       " 'KBQK',\n",
       " 'KBRD',\n",
       " 'KBRL',\n",
       " 'KBRO',\n",
       " 'KBTL',\n",
       " 'KBTM',\n",
       " 'KBTR',\n",
       " 'KBTV',\n",
       " 'KBUF',\n",
       " 'KBUR',\n",
       " 'KBVI',\n",
       " 'KBVX',\n",
       " 'KBVY',\n",
       " 'KBWG',\n",
       " 'KBWI',\n",
       " 'KBYI',\n",
       " 'KBZN',\n",
       " 'KCAE',\n",
       " 'KCAK',\n",
       " 'KCAR',\n",
       " 'KCDC',\n",
       " 'KCDR',\n",
       " 'KCDS',\n",
       " 'KCEC',\n",
       " 'KCEF',\n",
       " 'KCGI',\n",
       " 'KCGX',\n",
       " 'KCHA',\n",
       " 'KCHH',\n",
       " 'KCHO',\n",
       " 'KCHS',\n",
       " 'KCID',\n",
       " 'KCIU',\n",
       " 'KCKB',\n",
       " 'KCKL',\n",
       " 'KCLE',\n",
       " 'KCLL',\n",
       " 'KCLM',\n",
       " 'KCLT',\n",
       " 'KCMH',\n",
       " 'KCMI',\n",
       " 'KCMX',\n",
       " 'KCNM',\n",
       " 'KCNU',\n",
       " 'KCOD',\n",
       " 'KCOE',\n",
       " 'KCON',\n",
       " 'KCOS',\n",
       " 'KCOU',\n",
       " 'KCPR',\n",
       " 'KCRE',\n",
       " 'KCRP',\n",
       " 'KCRQ',\n",
       " 'KCRW',\n",
       " 'KCSG',\n",
       " 'KCSV',\n",
       " 'KCTB',\n",
       " 'KCVG',\n",
       " 'KCWA',\n",
       " 'KCYS',\n",
       " 'KDAB',\n",
       " 'KDAG',\n",
       " 'KDAL',\n",
       " 'KDAN',\n",
       " 'KDAY',\n",
       " 'KDBQ',\n",
       " 'KDCA',\n",
       " 'KDDC',\n",
       " 'KDEC',\n",
       " 'KDEN',\n",
       " 'KDET',\n",
       " 'KDFW',\n",
       " 'KDHN',\n",
       " 'KDHT',\n",
       " 'KDIK',\n",
       " 'KDLH',\n",
       " 'KDLS',\n",
       " 'KDMN',\n",
       " 'KDPA',\n",
       " 'KDRA',\n",
       " 'KDRO',\n",
       " 'KDRT',\n",
       " 'KDSM',\n",
       " 'KDTW',\n",
       " 'KDUG',\n",
       " 'KDUJ',\n",
       " 'KEAT',\n",
       " 'KEAU',\n",
       " 'KECG',\n",
       " 'KEED',\n",
       " 'KEGE',\n",
       " 'KEKN',\n",
       " 'KEKO',\n",
       " 'KEL',\n",
       " 'KELD',\n",
       " 'KELM',\n",
       " 'KELO',\n",
       " 'KELP',\n",
       " 'KELY',\n",
       " 'KENV',\n",
       " 'KEPH',\n",
       " 'KEPO',\n",
       " 'KEPZ',\n",
       " 'KERI',\n",
       " 'KESF',\n",
       " 'KEUG',\n",
       " 'KEVV',\n",
       " 'KEWB',\n",
       " 'KEWN',\n",
       " 'KEWR',\n",
       " 'KEYW',\n",
       " 'KFAM',\n",
       " 'KFAR',\n",
       " 'KFAT',\n",
       " 'KFAY',\n",
       " 'KFCA',\n",
       " 'KFDY',\n",
       " 'KFKL',\n",
       " 'KFLG',\n",
       " 'KFLL',\n",
       " 'KFLO',\n",
       " 'KFMN',\n",
       " 'KFMY',\n",
       " 'KFNT',\n",
       " 'KFOE',\n",
       " 'KFPR',\n",
       " 'KFRM',\n",
       " 'KFSD',\n",
       " 'KFSM',\n",
       " 'KFTW',\n",
       " 'KFTY',\n",
       " 'KFVE',\n",
       " 'KFVX',\n",
       " 'KFWA',\n",
       " 'KFXE',\n",
       " 'KFYV',\n",
       " 'KGAG',\n",
       " 'KGCC',\n",
       " 'KGCK',\n",
       " 'KGCN',\n",
       " 'KGEG',\n",
       " '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": [
    "### 3.2 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": [
    "[Top](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html)\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4 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": [
    "[Top](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html)\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5 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": [
    "[Top](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html)\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6 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": [
    "### 6.2 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": [
    "### 6.2 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": [
    "#### 6.2.1 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": [
    "#### 6.2.2 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": [
    "#### 6.2.3 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": [
    "[Top](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html)\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7 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": {},
   "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": [
    "[Top](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html)\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": [
    "[Top](https://unidata.github.io/python-awips/examples/generated/Model_Sounding_Data.html)\n",
    "\n",
    "---"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.5"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": false,
   "sideBar": false,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": false,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}