mirror of
https://github.com/Unidata/python-awips.git
synced 2025-02-24 06:57:56 -05:00
190 lines
121 KiB
Text
190 lines
121 KiB
Text
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The following notebook takes you through the stepd of retreiving an Upper Air vertical profile from an AWIPS EDEX server, and plotting with Matplotlib and MetPy.\n",
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"\n",
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"The **bufrua** plugin returns separate objects for parameters at **mandatory levels** and at **significant temperature levels**. For the SkewT/LogP plot, significant temperature levels are used to plot the pressure, temperature, and dewpoint lines, while mandatory levels are used to plot the wind profile."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"%matplotlib inline\n",
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"from awips.dataaccess import DataAccessLayer\n",
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"import matplotlib.tri as mtri\n",
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"import matplotlib.pyplot as plt\n",
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"from mpl_toolkits.axes_grid1.inset_locator import inset_axes\n",
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"import numpy as np\n",
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"import math\n",
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"from metpy.calc import get_wind_speed, get_wind_components, lcl, dry_lapse, parcel_profile\n",
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"from metpy.plots import SkewT, Hodograph\n",
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"from metpy.units import units, concatenate\n",
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"\n",
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"# Set EDEX host\n",
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"DataAccessLayer.changeEDEXHost(\"edex-cloud.unidata.ucar.edu\")\n",
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"request = DataAccessLayer.newDataRequest()\n",
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"\n",
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"# Data type bufrua\n",
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"request.setDatatype(\"bufrua\")\n",
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"availableLocs = DataAccessLayer.getAvailableLocationNames(request)\n",
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"availableLocs.sort()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"# Parameters\n",
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"MAN_PARAMS = set(['prMan', 'htMan', 'tpMan', 'tdMan', 'wdMan', 'wsMan'])\n",
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"SIGT_PARAMS = set(['prSigT', 'tpSigT', 'tdSigT'])\n",
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"request.setParameters(\"wmoStaNum\", \"validTime\", \"rptType\", \"staElev\", \"numMand\",\n",
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" \"numSigT\", \"numSigW\", \"numTrop\", \"numMwnd\", \"staName\")\n",
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"request.getParameters().extend(MAN_PARAMS)\n",
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"request.getParameters().extend(SIGT_PARAMS)\n",
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"\n",
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"station = \"72562\" # KLBF\n",
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"request.setLocationNames(station)\n",
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"\n",
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"datatimes = DataAccessLayer.getAvailableTimes(request)\n",
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"\n",
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"# Get most recent record\n",
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"response = DataAccessLayer.getGeometryData(request,times=datatimes[-2].validPeriod)\n",
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"\n",
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"# Initialize data arrays\n",
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"prMan,wdMan,wsMan = np.array([]),np.array([]),np.array([])\n",
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"prSig,tpSig,tdSig = np.array([]),np.array([]),np.array([])\n",
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"manGeos = []\n",
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"sigtGeos = []\n",
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"\n",
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"# Build ordered arrays\n",
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"for ob in response:\n",
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" if set(ob.getParameters()) & MAN_PARAMS:\n",
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" manGeos.append(ob)\n",
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" prMan = np.append(prMan,ob.getNumber(\"prMan\"))\n",
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" wdMan = np.append(wdMan,ob.getNumber(\"wdMan\"))\n",
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" wsMan = np.append(wsMan,ob.getNumber(\"wsMan\"))\n",
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" continue\n",
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" if set(ob.getParameters()) & SIGT_PARAMS:\n",
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" sigtGeos.append(ob)\n",
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" prSig = np.append(prSig,ob.getNumber(\"prSigT\"))\n",
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" tpSig = np.append(tpSig,ob.getNumber(\"tpSigT\"))\n",
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" tdSig = np.append(tdSig,ob.getNumber(\"tdSigT\"))\n",
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" continue"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"sounding_title = str(ob.getLocationName()) + \" \" + str(ob.getDataTime())\n",
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"\n",
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"# Need to sort mandatory (not sigT) levels because of the 1000.MB interpolation inclusion\n",
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"ps = prMan.argsort()[::-1]\n",
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"wpres = prMan[ps]\n",
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"direc = wdMan[ps]\n",
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"spd = wsMan[ps]\n",
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"\n",
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"prSig[prSig <= -9999] = np.nan\n",
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"tpSig[tpSig <= -9999] = np.nan\n",
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"tdSig[tdSig <= -9999] = np.nan\n",
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"wpres[wpres <= -9999] = np.nan\n",
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"direc[direc <= -9999] = np.nan\n",
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"spd[spd <= -9999] = np.nan\n",
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"\n",
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"u,v = get_wind_components(spd, np.deg2rad(direc))\n",
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"p = (prSig/100) * units.mbar\n",
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"wpres = (wpres/100) * units.mbar\n",
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"T = (tpSig-273.15) * units.degC\n",
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"Td = (tdSig-273.15) * units.degC"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<matplotlib.figure.Figure at 0x7f50dd00be90>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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|
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"# Create a skewT plot\n",
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"plt.rcParams['figure.figsize'] = (8, 10)\n",
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"skew = SkewT()\n",
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"\n",
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"# Plot the data using normal plotting functions, in this case using\n",
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"# log scaling in Y, as dictated by the typical meteorological plot\n",
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"skew.plot(p, T, 'r', linewidth=2)\n",
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"skew.plot(p, Td, 'g', linewidth=2)\n",
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"skew.plot_barbs(wpres, u, v)\n",
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"skew.ax.set_ylim(1000, 100)\n",
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"skew.ax.set_xlim(-30, 30)\n",
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"plt.title(sounding_title)\n",
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"\n",
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"# Calculate LCL height and plot as black dot\n",
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"l = lcl(p[0], T[0], Td[0])\n",
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"lcl_temp = dry_lapse(concatenate((p[0], l)), T[0])[-1].to('degC')\n",
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"skew.plot(l, lcl_temp, 'ko', markerfacecolor='black')\n",
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"\n",
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"# An example of a slanted line at constant T -- in this case the 0 isotherm\n",
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"l = skew.ax.axvline(0, color='c', linestyle='--', linewidth=2)\n",
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"\n",
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"# Draw hodograph\n",
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"ax_hod = inset_axes(skew.ax, '30%', '30%', loc=3)\n",
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"h = Hodograph(ax_hod, component_range=max(wsMan))\n",
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"h.add_grid(increment=20)\n",
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"h.plot_colormapped(u, v, spd)\n",
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"\n",
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"# Show the plot\n",
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"plt.show()"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 2",
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"language": "python",
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"name": "python2"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.10"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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