{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Reading Older NEXRAD Data and Fixing Latitude and Longitude Issues\n\nIn this example, we will show how to read in older NEXRAD files prior\nto 2008 that are missing some coordinate metadata.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "print(__doc__)\n\n\n# Author: Zachary Sherman (zsherman@anl.gov)\n# License: BSD 3 clause"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Import our required packages.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import cartopy.crs as ccrs\nimport matplotlib.pyplot as plt\n\nimport pyart"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Read older NEXRAD Level 2 Data\n\nOlder NEXRAD files prior to 2008, have the tendency to not contain some of\nthe required metadata for Py-ART's NEXRAD reader. This usually results in\nmissing latitude and longitude data, so after reading with Py-ART, both\ncoordinates have a value of 0. This example, we will show how to properly\nread in an older NEXRAD file.\n\nFirst we want to get an older file from amazon web service:\n\n   ``s3://unidata-nexrad-level2/year/month/date/radarsite/{radarsite}{year}{month}{date}_{hour}{minute}{second}.gz``\n\nWhere in our case, we are using a sample data file from Handford, CA (KHNX)\non July 24, 2006, at 0203:38 UTC. This means our path would look like this:\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "# Note: Older files do not contain the 'V06' but instead '.gz' in the AWS path.\n\naws_nexrad_level2_file = (\n    \"s3://unidata-nexrad-level2/2006/07/24/KHNX/KHNX20060724_020338.gz\"\n)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "We can use the **pyart.io.read_nexrad_archive** module to access our data, passing in the filepath.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "radar = pyart.io.read_nexrad_archive(aws_nexrad_level2_file)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Now let us take a look at the radar latitude and longitude data.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "print(radar.latitude[\"data\"])\nprint(radar.longitude[\"data\"])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "This is clearly not correct! The problem is the reader could not find the\nmetadata (message 31) for the coordinates.\n\nLucky for us, we can provide the station in Py-ART's NEXRAD reader, which will\npull the coordinate information from a dictionary found within Py-ART.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "radar = pyart.io.read_nexrad_archive(aws_nexrad_level2_file, station=\"KHNX\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Again, let us take a look at the radar latitude and longitude data.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "print(radar.latitude[\"data\"])\nprint(radar.longitude[\"data\"])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Everything now looks correct as this is in Handford CA!\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "# We can create a plot as well utilizing Cartopy to see how it looks.\ndisplay = pyart.graph.RadarMapDisplay(radar)\n\n# Setting projection and ploting the first tilt.\nprojection = ccrs.LambertConformal(\n    central_latitude=radar.latitude[\"data\"][0],\n    central_longitude=radar.longitude[\"data\"][0],\n)\n\nfig = plt.figure(figsize=(6, 6))\ndisplay.plot_ppi_map(\n    \"reflectivity\", 0, vmin=-20, vmax=54, projection=projection, resolution=\"10m\"\n)"
      ]
    }
  ],
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