2018-09-05 15:52:38 -06:00
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
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"The EDEX modelsounding plugin creates 64-level vertical profiles from GFS and ETA (NAM) BUFR products distirubted over NOAAport. Paramters which are requestable are **pressure**, **temperature**, **specHum**, **uComp**, **vComp**, **omega**, **cldCvr**."
]
},
{
"cell_type": "code",
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"execution_count": 1,
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"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"from awips.dataaccess import DataAccessLayer\n",
"import matplotlib.tri as mtri\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 get_wind_components, lcl, dry_lapse, parcel_profile, dewpoint\n",
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"from metpy.calc import wind_speed, wind_direction, thermo, vapor_pressure\n",
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"from metpy.plots import SkewT, Hodograph\n",
"from metpy.units import units, concatenate\n",
"\n",
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"DataAccessLayer.changeEDEXHost(\"edex-cloud.unidata.ucar.edu\")\n",
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"request = DataAccessLayer.newDataRequest()\n",
"request.setDatatype(\"modelsounding\")\n",
"forecastModel = \"GFS\"\n",
"request.addIdentifier(\"reportType\", forecastModel)\n",
"request.setParameters(\"pressure\",\"temperature\",\"specHum\",\"uComp\",\"vComp\",\"omega\",\"cldCvr\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Available Locations"
]
},
{
"cell_type": "code",
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"execution_count": 2,
2018-09-05 15:52:38 -06:00
"metadata": {},
"outputs": [
{
"data": {
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2018-10-09 13:39:16 -06:00
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" '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",
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" ...]"
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]
},
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"execution_count": 2,
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"locations = DataAccessLayer.getAvailableLocationNames(request)\n",
"locations.sort()\n",
"list(locations)"
]
},
{
"cell_type": "code",
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"execution_count": 3,
"metadata": {},
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"outputs": [],
"source": [
"request.setLocationNames(\"KFRM\")\n",
"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": [
"## Model Sounding Parameters\n",
"\n",
"Construct arrays for each parameter to plot (temperature, pressure, moisutre (spec. humidity), wind components, and cloud cover)"
]
},
{
"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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"parms = ['temperature', 'pressure', 'vComp', 'uComp', 'cldCvr', 'specHum', 'omega']\n",
"site = KFRM\n",
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"geom = POINT (-94.41999816894531 43.65000152587891)\n",
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"datetime = 2018-10-09 12:00:00\n",
"reftime = Oct 09 18 12:00:00 GMT\n",
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"fcstHour = 0\n",
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"period = (Oct 09 18 12:00:00 , Oct 09 18 12:00:00 )\n"
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]
}
],
"source": [
"tmp,prs,sh = np.array([]),np.array([]),np.array([])\n",
"uc,vc,om,cld = np.array([]),np.array([]),np.array([]),np.array([])\n",
"\n",
"for ob in response:\n",
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" tmp = np.append(tmp,ob.getNumber(\"temperature\"))\n",
" prs = np.append(prs,ob.getNumber(\"pressure\"))\n",
" sh = np.append(sh,ob.getNumber(\"specHum\"))\n",
" uc = np.append(uc,ob.getNumber(\"uComp\"))\n",
" vc = np.append(vc,ob.getNumber(\"vComp\"))\n",
" om = np.append(om,ob.getNumber(\"omega\"))\n",
" cld = np.append(cld,ob.getNumber(\"cldCvr\"))\n",
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"\n",
"print(\"parms = \" + str(ob.getParameters()))\n",
"print(\"site = \" + str(ob.getLocationName()))\n",
"print(\"geom = \" + str(ob.getGeometry()))\n",
"print(\"datetime = \" + str(ob.getDataTime()))\n",
"print(\"reftime = \" + str(ob.getDataTime().getRefTime()))\n",
"print(\"fcstHour = \" + str(ob.getDataTime().getFcstTime()))\n",
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"print(\"period = \" + str(ob.getDataTime().getValidPeriod()))"
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]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Calculating 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",
"**1) MetPy calculated mixing ratio and vapor pressure**"
]
},
{
"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
"source": [
"t = (tmp-273.15) * units.degC\n",
"p = prs/100 * units.mbar\n",
"\n",
"u,v = uc*1.94384,vc*1.94384 # m/s to knots\n",
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"spd = wind_speed(u, v) * units.knots\n",
"dir = wind_direction(u, v) * units.deg"
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]
},
{
"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/mjames/miniconda3/envs/python3-awips/lib/python3.6/site-packages/metpy/calc/thermo.py:690: RuntimeWarning: divide by zero encountered in log\n",
" val = np.log(e / sat_pressure_0c)\n",
"/Users/mjames/miniconda3/envs/python3-awips/lib/python3.6/site-packages/pint/quantity.py:1403: RuntimeWarning: divide by zero encountered in log\n",
" out = uf(*mobjs)\n",
"/Users/mjames/miniconda3/envs/python3-awips/lib/python3.6/site-packages/pint/quantity.py:802: RuntimeWarning: invalid value encountered in true_divide\n",
" magnitude = magnitude_op(new_self._magnitude, other._magnitude)\n"
]
}
],
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"source": [
"rmix = (sh/(1-sh)) *1000 * units('g/kg')\n",
"e = vapor_pressure(p, rmix)\n",
"td = dewpoint(e)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**2) metpy calculated assuming spec. humidity = mixing ratio**"
]
},
{
"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [],
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"source": [
"td2 = dewpoint(vapor_pressure(p, sh))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**3) NCEP AWIPS soundingrequest plugin**\n",
"\n",
"based on GEMPAK/NSHARP, from 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",
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"execution_count": 8,
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"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
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"/Users/mjames/miniconda3/envs/python3-awips/lib/python3.6/site-packages/ipykernel_launcher.py:8: RuntimeWarning: divide by zero encountered in log\n",
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" \n",
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"/Users/mjames/miniconda3/envs/python3-awips/lib/python3.6/site-packages/ipykernel_launcher.py:8: RuntimeWarning: invalid value encountered in true_divide\n",
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" \n"
]
}
],
"source": [
"# new arrays\n",
"ntmp = tmp\n",
"\n",
"# where p=pressure(pa), T=temp(C), T0=reference temp(273.16)\n",
"rh = 0.263*prs*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": [
"## MetPy SkewT and Hodograph"
]
},
{
"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
"outputs": [
{
"data": {
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"image/png": "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"text/plain": [
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"<Figure size 864x1008 with 2 Axes>"
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]
},
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"metadata": {
"needs_background": "light"
},
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"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"\n",
"plt.rcParams['figure.figsize'] = (12, 14)\n",
"\n",
"# Create a skewT plot\n",
"skew = SkewT()\n",
"\n",
"# Plot the data\n",
"skew.plot(p, t, 'r', linewidth=2)\n",
"skew.plot(p, td, 'b', linewidth=2)\n",
"skew.plot(p, td2, 'y')\n",
"skew.plot(p, dwpc, 'g', linewidth=2)\n",
"\n",
"skew.plot_barbs(p, u, v)\n",
"skew.ax.set_ylim(1000, 100)\n",
"skew.ax.set_xlim(-40, 60)\n",
"\n",
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"plt.title( forecastModel + \" \" \\\n",
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" + ob.getLocationName() \\\n",
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" + \"(\"+ str(ob.getGeometry()) + \")\" \\\n",
" + \", \" + str(ob.getDataTime())\n",
")\n",
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"\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=2)\n",
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"h = Hodograph(ax_hod, component_range=wind_speed(u, v).max())\n",
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"h.add_grid(increment=20)\n",
"h.plot_colormapped(u, v, spd)\n",
"\n",
"# Show the plot\n",
"plt.show()"
]
}
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