WSR88D_4panel_AWS.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This program downloads data from the Amazon cloud and produces a 4-panel plot. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "##Run this cell first, this loads/compiles the needed modules/functions\n",
    "%matplotlib inline\n",
    "from boto.s3.connection import S3Connection\n",
    "import gzip\n",
    "from matplotlib import pyplot as plt\n",
    "import shutil, os\n",
    "from datetime import timedelta, datetime\n",
    "import numpy as np\n",
    "import tempfile\n",
    "import pyart\n",
    "import cartopy.crs as ccrs\n",
    "def nearestDate(dates, pivot):\n",
    "    return min(dates, key=lambda x: abs(x - pivot))\n",
    "\n",
    "\n",
    "def get_radar_from_aws(site, datetime_t):\n",
    "    \"\"\"\n",
    "    Get the closest volume of NEXRAD data to a particular datetime.\n",
    "    Parameters\n",
    "    ----------\n",
    "    site : string\n",
    "        four letter radar designation \n",
    "    datetime_t : datetime\n",
    "        desired date time\n",
    "    \"\"\"\n",
    "    \n",
    "    #First create the query string for the bucket knowing\n",
    "    #how NOAA and AWS store the data\n",
    "    \n",
    "    my_pref = datetime_t.strftime('%Y/%m/%d/') + site\n",
    "    \n",
    "    #Connect to the bucket\n",
    "    \n",
    "    conn = S3Connection(anon = True)\n",
    "    bucket = conn.get_bucket('noaa-nexrad-level2')\n",
    "    \n",
    "    #Get a list of files \n",
    "    \n",
    "    bucket_list = list(bucket.list(prefix = my_pref))\n",
    "    #print(bucket_list)\n",
    "    #we are going to create a list of keys and datetimes to allow easy searching\n",
    "    #print bucket_list\n",
    "    keys = []\n",
    "    datetimes = []\n",
    "    \n",
    "    #populate the list\n",
    "\n",
    "    for i in range(len(bucket_list)):\n",
    "        this_str = str(bucket_list[i].key)\n",
    "        if 'gz' in this_str:\n",
    "            endme = this_str[-22:-3]\n",
    "            fmt = '%Y%m%d_%H%M%S_V06' \n",
    "            dt = datetime.strptime(endme, fmt)\n",
    "            datetimes.append(dt)\n",
    "            keys.append(bucket_list[i])\n",
    "            #print(dt)\n",
    "        if this_str[-3::] == 'V06': #'LSX20160707_000150_' does not match format '%Y%m%d_%H%M%S_V06'\n",
    "            #print(this_str)\n",
    "            #print(this_str[-19::])\n",
    "            endme = this_str[-19::]\n",
    "            fmt = '%Y%m%d_%H%M%S_V06' \n",
    "            dt = datetime.strptime(endme, fmt)\n",
    "            datetimes.append(dt)\n",
    "            keys.append(bucket_list[i])\n",
    "    \n",
    "    #function to allow easy searching \n",
    "    \n",
    "    def func(x):\n",
    "        delta =  x - datetime_t if x > datetime_t else timedelta.max\n",
    "        return delta\n",
    "    \n",
    "    #find the closest available radar to your datetime \n",
    "    \n",
    "    closest_datetime = nearestDate(datetimes, datetime_t)\n",
    "    index = datetimes.index(closest_datetime)\n",
    "    #print(closest_datetime)\n",
    "    #create a temp file, download radar data to file from S3\n",
    "    #read into a radar object and return\n",
    "    \n",
    "    localfile = tempfile.NamedTemporaryFile(delete=False)\n",
    "    keys[index].get_contents_to_filename(localfile.name)\n",
    "    radar = pyart.io.read(localfile.name)\n",
    "    name_str = str(bucket_list[index].key)\n",
    "    return (radar,name_str[-22:-4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "## This section imports modules needed to run the code\n",
    "b_d = datetime(2013,5,31,23,14) #datetime.utcnow() #datetime.strptime(base_date, fmt)\n",
    "radar_name='KTLX'\n",
    "my_radar = get_radar_from_aws(radar_name,b_d)\n",
    "\n",
    "center_lon=my_radar[0].longitude['data'][0] #Grab center coordinates of radar\n",
    "center_lat=my_radar[0].latitude['data'][0]  #Grab center coordinates of radar\n",
    "\n",
    "#Alternatively, you can use the lines below to specify the center coordinates\n",
    "#center_lon=-97\n",
    "#center_lat=48\n",
    "\n",
    "#Define range around center coordinates to plot.  This is in degrees latitude/longitude\n",
    "min_lat = center_lat-0.8\n",
    "max_lat = center_lat+0.8\n",
    "min_lon = center_lon-0.8\n",
    "max_lon = center_lon+0.8\n",
    "max_v=my_radar[0].fields['velocity']['data'].max()\n",
    "display = pyart.graph.RadarMapDisplay(my_radar[0])\n",
    "\n",
    "#Create Title for Plot\n",
    "time_str = pyart.graph.common.generate_radar_time_begin(my_radar[0]).isoformat()\n",
    "time_str = time_str[0:16]+'Z'\n",
    "fixed_angle = my_radar[0].fixed_angle['data'][0]\n",
    "figtitle = \"%s %.1f Deg. %s \" % (pyart.graph.common.generate_radar_name(my_radar[0]), fixed_angle,time_str)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "projection = ccrs.PlateCarree()\n",
    "fig = plt.figure(figsize=(10, 10),dpi=600)  #Create figure\n",
    "ax1 = fig.add_subplot(221,projection=projection) \n",
    "display.plot_ppi_map('reflectivity', 0, vmin=20, vmax=70,\n",
    "                     min_lon=min_lon, max_lon=max_lon, min_lat=min_lat, max_lat=max_lat,\n",
    "                     resolution='10m', projection=projection,colorbar_flag=1,\n",
    "                     fig=fig, lat_0=center_lat,\n",
    "                     lon_0=center_lon,title = 'Z',colorbar_label='Equivalent Reflectivity Factor (dBZ)')\n",
    "display.plot_point(center_lon, center_lat)\n",
    "ax2 = fig.add_subplot(222,projection=projection) \n",
    "display.plot_ppi_map('differential_reflectivity', 0, vmin=-2, vmax=6,\n",
    "                     min_lon=min_lon, max_lon=max_lon, min_lat=min_lat, max_lat=max_lat,\n",
    "                     resolution='10m', projection=projection,colorbar_flag=1,\n",
    "                     fig=fig, lat_0=center_lat,\n",
    "                     lon_0=center_lon,title = 'ZDR',colorbar_label='Log Differential Reflectivity Factor (dBZ)')\n",
    "display.plot_point(center_lon, center_lat)\n",
    "ax3 = fig.add_subplot(223,projection=projection) \n",
    "display.plot_ppi_map('cross_correlation_ratio', 0, vmin=0.2, vmax=1,\n",
    "                     min_lon=min_lon, max_lon=max_lon, min_lat=min_lat, max_lat=max_lat,\n",
    "                     resolution='10m', projection=projection,colorbar_flag=1,\n",
    "                     fig=fig, lat_0=center_lat,\n",
    "                     lon_0=center_lon,title = 'CC',colorbar_label='Cross Correlation Ratio (ratio)')\n",
    "display.plot_point(center_lon, center_lat)\n",
    "ax4 = fig.add_subplot(224,projection=projection) \n",
    "display.plot_ppi_map('velocity', 1, vmin=-0.9*max_v, vmax=0.9*max_v,\n",
    "                     min_lon=min_lon, max_lon=max_lon, min_lat=min_lat, max_lat=max_lat,\n",
    "                     resolution='10m', projection=projection,colorbar_flag=1,\n",
    "                     fig=fig, lat_0=center_lat,\n",
    "                     lon_0=center_lon,title = 'V',colorbar_label='Radial Velocity (m/s)')\n",
    "display.plot_point(center_lon, center_lat)\n",
    "plt.savefig('output//'+my_radar[1]+'.png',dpi=300) #saves file to image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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