{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "1c689d8a-3398-4312-b621-2b5730c01be3",
   "metadata": {},
   "source": [
    "# Hail Storm Visualization Using Py-ART and Pandas!\n",
    "\n",
    "Within this post, we will walk through how to combine radar and storm report data, creating an animation of the two!\n",
    "\n",
    "## Motivation\n",
    "\n",
    "On September 7, 2021, a strong line of thunderstorms passed through Southern Wisconsin and Northern Illinois, leaving a trail of hail and wind damage in its path.\n",
    "\n",
    "Here is a sample image of the storm reports and hail that was found near the Milwaukee/Madison area in Wisconsin\n",
    "\n",
    "\n",
    "\n",
    "![Hail Image](https://www.weather.gov/images/mkx/events/2021/Sept_07_Hail/RecapOfSevereStorms.png)\n",
    "\n",
    "We would like to add some more context here. Specifically, we would like to add reflectivity imagery from the NOAA radar network (NEXRAD), with corresponding storm reports paired in time.\n",
    "\n",
    "This notebooks build upon a notebook Russ Schumacher from Colorado State Unversity put together for his class\n",
    "- [Link to original notebook](https://github.com/russ-schumacher/ats641_spring2022/blob/master/example_notebooks/pyart_nexrad_maps_reports.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1fb5cfe1-1047-48fd-bc52-2385be786e99",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b91a79eb-1c0f-46d9-af5c-6c8b39412af1",
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "import glob\n",
    "from math import atan2 as atan2\n",
    "import os\n",
    "import tempfile\n",
    "import warnings\n",
    "\n",
    "import fsspec\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cfeature\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.colors as mcolors\n",
    "import matplotlib.dates as mdates\n",
    "from metpy.plots import USCOUNTIES\n",
    "import imageio\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pyart\n",
    "import nexradaws\n",
    "import pytz\n",
    "\n",
    "templocation = tempfile.mkdtemp()\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f45ee30b-0138-4c6c-a451-bb953d7e7959",
   "metadata": {},
   "source": [
    "## NEXRAD Data Access - fsspec\n",
    "Let's start by taking a look at the radar data available from the NEXRAD (NOAA's weather radar network) archive on the Amazon Cloud.\n",
    "\n",
    "We can use [`fsspec`](https://filesystem-spec.readthedocs.io/en/latest/), which is a Python package focused on working across different filesystems (ex. your local machine vs. the different clouds)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26dca10d-74b8-45ba-b361-c290650558cc",
   "metadata": {},
   "source": [
    "### Setup the Filesystem and Read From the Bucket\n",
    "We start by setting up our Amazon bucket, setting anonymous access."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "56b0b966-59f2-400e-80f3-7439c447866d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['noaa-nexrad-level2/2021/09/07/KMKX/KMKX20210907_170101_V06',\n",
       " 'noaa-nexrad-level2/2021/09/07/KMKX/KMKX20210907_170739_V06',\n",
       " 'noaa-nexrad-level2/2021/09/07/KMKX/KMKX20210907_171431_V06',\n",
       " 'noaa-nexrad-level2/2021/09/07/KMKX/KMKX20210907_172123_V06',\n",
       " 'noaa-nexrad-level2/2021/09/07/KMKX/KMKX20210907_172814_V06',\n",
       " 'noaa-nexrad-level2/2021/09/07/KMKX/KMKX20210907_173452_V06',\n",
       " 'noaa-nexrad-level2/2021/09/07/KMKX/KMKX20210907_174130_V06',\n",
       " 'noaa-nexrad-level2/2021/09/07/KMKX/KMKX20210907_174807_V06',\n",
       " 'noaa-nexrad-level2/2021/09/07/KMKX/KMKX20210907_175459_V06',\n",
       " 'noaa-nexrad-level2/2021/09/07/KMKX/KMKX20210907_175459_V06_MDM']"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fs = fsspec.filesystem(\"s3\", anon=True)\n",
    "\n",
    "date = datetime(2021, 9, 7, 17)\n",
    "site = \"KMKX\"\n",
    "\n",
    "nexrad_path = date.strftime(f\"s3://noaa-nexrad-level2/%Y/%m/%d/{site}/{site}%Y%m%d_%H*\")\n",
    "files = sorted(fs.glob(nexrad_path))\n",
    "files"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e18b53ae-c852-40df-8877-bc2ae517599a",
   "metadata": {},
   "source": [
    "### Read in a File\n",
    "Let's read the first file using `pyart.io.read_nexrad_archive`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "f5a7d061-ead1-4f57-9243-0186bc6230cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "radar = pyart.io.read_nexrad_archive(\"s3://\" + files[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41d9e81a-4eb5-4fc7-9ebb-415b929fcac3",
   "metadata": {},
   "source": [
    "### Visualize the Dataset\n",
    "We can start by visualizing the reflectivity field, which indicates heavy precipitation, with possibly hail!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "85db2f77-10f6-4d3d-bcac-2954c6a08222",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display = pyart.graph.RadarMapDisplay(radar)\n",
    "ax = plt.subplot(111, projection=ccrs.PlateCarree())\n",
    "\n",
    "ax.add_feature(cfeature.STATES, linewidth=3)\n",
    "ax.add_feature(USCOUNTIES, alpha=0.4)\n",
    "\n",
    "display.plot_ppi_map(\n",
    "    \"reflectivity\",\n",
    "    ax=ax,\n",
    "    embellish=False,\n",
    "    add_grid_lines=True,\n",
    "    cmap=\"pyart_ChaseSpectral\",\n",
    "    vmin=-20,\n",
    "    vmax=70,\n",
    ")\n",
    "\n",
    "ax.set_extent((-90, -87, 41, 44))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b881dae-3c5f-4987-822d-45a060f6f311",
   "metadata": {},
   "source": [
    "## Read in NEXRAD Data Using `nexradaws`\n",
    "There is a package, `nexradaws`, which makes searching and downloading data from the cloud much easier!\n",
    "\n",
    "Let's look at using this instead of scrolling the filesystem."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3e64afc-8091-4d40-8c11-a92f207ca257",
   "metadata": {},
   "source": [
    "### Configure the Search\n",
    "We need to specify which radar (in this case, we are interested in Milwaukee (KMKX), Wisconsin)\n",
    "\n",
    "The storm moved through the region between 15 and 20 UTC on September 7, 2021.\n",
    "\n",
    "We also set the minimum and maximum latitudes/longitudes to plot, based on the image above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "47d29f22-3ed4-46fe-8f68-0fd433e0a6ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "radar_id = \"KMKX\"\n",
    "start = pd.Timestamp(2021, 9, 7, 15).tz_localize(tz=\"UTC\")\n",
    "end = pd.Timestamp(2021, 9, 7, 20).tz_localize(tz=\"UTC\")\n",
    "\n",
    "\n",
    "min_lon = -90\n",
    "max_lon = -87\n",
    "min_lat = 41\n",
    "max_lat = 44"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83932588-718a-44fe-a605-5dfd5fe66a86",
   "metadata": {},
   "source": [
    "### Search and Download the Data\n",
    "We will download the data in this case since we would like to store it for later!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "eaab88cb-92c1-4143-8e34-50a582ba0632",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 54 scans available between 2021-09-07 15:00:00+00:00 and 2021-09-07 20:00:00+00:00\n",
      "\n",
      "Downloaded KMKX20210907_151132_V06\n",
      "Downloaded KMKX20210907_152621_V06\n",
      "Downloaded KMKX20210907_150152_V06\n",
      "Downloaded KMKX20210907_151622_V06\n",
      "Downloaded KMKX20210907_152121_V06\n",
      "Downloaded KMKX20210907_150642_V06\n",
      "Downloaded KMKX20210907_155424_V06_MDM\n",
      "Downloaded KMKX20210907_153610_V06\n",
      "Downloaded KMKX20210907_154814_V06\n",
      "Downloaded KMKX20210907_155424_V06\n",
      "Downloaded KMKX20210907_154205_V06\n",
      "Downloaded KMKX20210907_160034_V06\n",
      "Downloaded KMKX20210907_160607_V06\n",
      "Downloaded KMKX20210907_161141_V06\n",
      "Downloaded KMKX20210907_163532_V06\n",
      "Downloaded KMKX20210907_161714_V06\n",
      "Downloaded KMKX20210907_162924_V06\n",
      "Downloaded KMKX20210907_164816_V06\n",
      "Downloaded KMKX20210907_165433_V06\n",
      "Downloaded KMKX20210907_165433_V06_MDM\n",
      "Downloaded KMKX20210907_162247_V06\n",
      "Downloaded KMKX20210907_171431_V06\n",
      "Downloaded KMKX20210907_153134_V06\n",
      "Downloaded KMKX20210907_170739_V06\n",
      "Downloaded KMKX20210907_172814_V06\n",
      "Downloaded KMKX20210907_173452_V06\n",
      "Downloaded KMKX20210907_174130_V06\n",
      "Downloaded KMKX20210907_172123_V06\n",
      "Downloaded KMKX20210907_164149_V06\n",
      "Downloaded KMKX20210907_174807_V06\n",
      "Downloaded KMKX20210907_175459_V06_MDM\n",
      "Downloaded KMKX20210907_175459_V06\n",
      "Downloaded KMKX20210907_182057_V06\n",
      "Downloaded KMKX20210907_170101_V06\n",
      "Downloaded KMKX20210907_182749_V06\n",
      "Downloaded KMKX20210907_184048_V06\n",
      "Downloaded KMKX20210907_180841_V06\n",
      "Downloaded KMKX20210907_183440_V06\n",
      "Downloaded KMKX20210907_185431_V06_MDM\n",
      "Downloaded KMKX20210907_181448_V06\n",
      "Downloaded KMKX20210907_180150_V06\n",
      "Downloaded KMKX20210907_185431_V06\n",
      "Downloaded KMKX20210907_190109_V06\n",
      "Downloaded KMKX20210907_190703_V06\n",
      "Downloaded KMKX20210907_193238_V06\n",
      "Downloaded KMKX20210907_191951_V06\n",
      "Downloaded KMKX20210907_191327_V06\n",
      "Downloaded KMKX20210907_195642_V06\n",
      "Downloaded KMKX20210907_194459_V06\n",
      "Downloaded KMKX20210907_195642_V06_MDM\n",
      "Downloaded KMKX20210907_193849_V06\n",
      "Downloaded KMKX20210907_184739_V06\n",
      "Downloaded KMKX20210907_192614_V06\n",
      "Downloaded KMKX20210907_195056_V06\n",
      "54 out of 54 files downloaded...0 errors\n"
     ]
    }
   ],
   "source": [
    "# Configure the nexrad interface using our time and location\n",
    "conn = nexradaws.NexradAwsInterface()\n",
    "scans = conn.get_avail_scans_in_range(start, end, radar_id)\n",
    "print(\"There are {} scans available between {} and {}\\n\".format(len(scans), start, end))\n",
    "\n",
    "# Download the files\n",
    "results = conn.download(scans, templocation)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d335d0fa-1612-49e1-a480-6c669a969463",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Read SPC Reports Using Pandas\n",
    "Now that we have our radar data, we can add Storm Prediction Center (SPC) reports for additional context. The SPC reports are categorized by\n",
    "- Wind\n",
    "- Hail\n",
    "- Tornado\n",
    "\n",
    "In this case, there were wind and hail reports reported to the local National Weather Service office in Milwaukee, that are accesible in the SPC report archive.\n",
    "\n",
    "The files are accesible via the internet using the following URL string\n",
    "- `https://www.spc.noaa.gov/wcm/data/{year}_{category}.csv`\n",
    "\n",
    "for example, the wind reports from 2021 can be found at\n",
    "- [`https://www.spc.noaa.gov/wcm/data/2021_wind.csv`](https://www.spc.noaa.gov/wcm/data/2021_wind.csv)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9dcbaeea-c27f-4756-9542-4f498d2bb4d3",
   "metadata": {},
   "source": [
    "### Setup a Function to Read the Reports\n",
    "Since the only variable that changes is the category and year, we can configure a function to help us generalize the code!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "8d33b813-7aef-4d7d-bb81-61c24dfe796f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_spc_reports(start_time, end_time, hazard, timezone=\"Etc/GMT+6\"):\n",
    "    \"\"\"\n",
    "    Reads in SPC report data remotely from the SPC\n",
    "    archive\n",
    "\n",
    "\n",
    "    ==========\n",
    "    Parameters\n",
    "    ==========\n",
    "    start_time: datetime.datetime, start time of interest\n",
    "    end_time: datetime.datetime, end time of interest\n",
    "    hazard: str, hazard of interest (hail, wind, or torn)\n",
    "    timezone: str, timezone of interest, default is US central time\n",
    "\n",
    "    ==========\n",
    "    Returns\n",
    "    ==========\n",
    "    df: pandas.DataFrame with the data\n",
    "    \"\"\"\n",
    "\n",
    "    # Read in the reports from the SPC archive\n",
    "    reports = pd.read_csv(\n",
    "        f\"https://www.spc.noaa.gov/wcm/data/{start_time.year}_{hazard}.csv\"\n",
    "    )\n",
    "\n",
    "    # Conver to datetime using the date and time columns\n",
    "    reports[\"datetime\"] = pd.to_datetime(reports.date + \" \" + reports.time)\n",
    "    reports.set_index(\"datetime\", inplace=True)\n",
    "\n",
    "    # Convert from local time to UTC time\n",
    "    reports.index = reports.index.tz_localize(\n",
    "        timezone, ambiguous=\"NaT\", nonexistent=\"shift_forward\"\n",
    "    ).tz_convert(\"UTC\")\n",
    "\n",
    "    # Subset down to 30 minutes before/after the radar times we're plotting\n",
    "    reports[\n",
    "        ((start_time - pd.Timedelta(minutes=30)).strftime(\"%Y-%m-%d %H:%M\")) : (\n",
    "            (end_time + pd.Timedelta(minutes=30)).strftime(\"%Y-%m-%d %H:%M\")\n",
    "        )\n",
    "    ]\n",
    "\n",
    "    return reports"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "976b71b9-6e18-4c98-9dc5-ea37ec17bb38",
   "metadata": {},
   "source": [
    "#### Read in the Reports\n",
    "Now that we have our function, we can read in the reports and assign to different dataframes!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "e6c189c1-2b14-4dda-8197-9af5535ca38b",
   "metadata": {},
   "outputs": [
    {
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       "      <th>2021-01-07 00:05:00+00:00</th>\n",
       "      <td>657523</td>\n",
       "      <td>2021</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>2021-01-06</td>\n",
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       "      <th>2021-01-07 00:21:00+00:00</th>\n",
       "      <td>657524</td>\n",
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       "      <td>663778</td>\n",
       "      <td>2021</td>\n",
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       "      <th>2021-12-30 22:10:00+00:00</th>\n",
       "      <td>663779</td>\n",
       "      <td>2021</td>\n",
       "      <td>12</td>\n",
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       "      <td>2021-12-30</td>\n",
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       "      <th>2021-12-30 22:42:00+00:00</th>\n",
       "      <td>663780</td>\n",
       "      <td>2021</td>\n",
       "      <td>12</td>\n",
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       "      <td>2021-12-30</td>\n",
       "      <td>16:42:00</td>\n",
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       "    <tr>\n",
       "      <th>2021-12-30 23:35:00+00:00</th>\n",
       "      <td>663781</td>\n",
       "      <td>2021</td>\n",
       "      <td>12</td>\n",
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       "      <td>2021-12-30</td>\n",
       "      <td>17:35:00</td>\n",
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       "</table>\n",
       "<p>6261 rows × 28 columns</p>\n",
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      ],
      "text/plain": [
       "                               om    yr  mo  dy        date      time  tz  st  \\\n",
       "datetime                                                                        \n",
       "2021-01-06 17:53:00+00:00  657521  2021   1   6  2021-01-06  11:53:00   3  TX   \n",
       "2021-01-06 23:31:00+00:00  657522  2021   1   6  2021-01-06  17:31:00   3  TX   \n",
       "2021-01-07 00:05:00+00:00  657523  2021   1   6  2021-01-06  18:05:00   3  TX   \n",
       "2021-01-07 00:21:00+00:00  657524  2021   1   6  2021-01-06  18:21:00   3  TX   \n",
       "2021-01-24 18:00:00+00:00  657525  2021   1  24  2021-01-24  12:00:00   3  AZ   \n",
       "...                           ...   ...  ..  ..         ...       ...  ..  ..   \n",
       "2021-12-30 21:45:00+00:00  663777  2021  12  30  2021-12-30  15:45:00   3  SC   \n",
       "2021-12-30 22:05:00+00:00  663778  2021  12  30  2021-12-30  16:05:00   3  SC   \n",
       "2021-12-30 22:10:00+00:00  663779  2021  12  30  2021-12-30  16:10:00   3  SC   \n",
       "2021-12-30 22:42:00+00:00  663780  2021  12  30  2021-12-30  16:42:00   3  SC   \n",
       "2021-12-30 23:35:00+00:00  663781  2021  12  30  2021-12-30  17:35:00   3  SC   \n",
       "\n",
       "                           stf  stn  ...      elon  len  wid  ns  sn  sg   f1  \\\n",
       "datetime                             ...                                        \n",
       "2021-01-06 17:53:00+00:00   48    0  ...  -96.7500    0    0   0   0   0  331   \n",
       "2021-01-06 23:31:00+00:00   48    0  ...  -95.4300    0    0   0   0   0   39   \n",
       "2021-01-07 00:05:00+00:00   48    0  ...  -95.0500    0    0   0   0   0  167   \n",
       "2021-01-07 00:21:00+00:00   48    0  ...  -95.0200    0    0   0   0   0  167   \n",
       "2021-01-24 18:00:00+00:00    4    0  ... -111.1595    0    0   0   0   0   19   \n",
       "...                        ...  ...  ...       ...  ...  ...  ..  ..  ..  ...   \n",
       "2021-12-30 21:45:00+00:00   45    0  ...  -80.0100    0    0   0   0   0   15   \n",
       "2021-12-30 22:05:00+00:00   45    0  ...  -80.1800    0    0   0   0   0   35   \n",
       "2021-12-30 22:10:00+00:00   45    0  ...  -80.2200    0    0   0   0   0   35   \n",
       "2021-12-30 22:42:00+00:00   45    0  ...  -81.1900    0    0   0   0   0   49   \n",
       "2021-12-30 23:35:00+00:00   45    0  ...  -80.1100    0    0   0   0   0   15   \n",
       "\n",
       "                           f2  f3  f4  \n",
       "datetime                               \n",
       "2021-01-06 17:53:00+00:00   0   0   0  \n",
       "2021-01-06 23:31:00+00:00   0   0   0  \n",
       "2021-01-07 00:05:00+00:00   0   0   0  \n",
       "2021-01-07 00:21:00+00:00   0   0   0  \n",
       "2021-01-24 18:00:00+00:00   0   0   0  \n",
       "...                        ..  ..  ..  \n",
       "2021-12-30 21:45:00+00:00   0   0   0  \n",
       "2021-12-30 22:05:00+00:00   0   0   0  \n",
       "2021-12-30 22:10:00+00:00   0   0   0  \n",
       "2021-12-30 22:42:00+00:00   0   0   0  \n",
       "2021-12-30 23:35:00+00:00   0   0   0  \n",
       "\n",
       "[6261 rows x 28 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wind_reports = read_spc_reports(start, end, \"wind\")\n",
    "tornado_reports = read_spc_reports(start, end, \"torn\")\n",
    "hail_reports = read_spc_reports(start, end, \"hail\")\n",
    "hail_reports"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc71b97a-59b1-4fa3-bfd8-df97dc8a9220",
   "metadata": {},
   "source": [
    "## Loop Through and Plot the Radar and Reports\n",
    "Let's put it all together! We can loop through and plot the radar image with corresponding wind reports."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8fd0e2cb-cd9b-4448-b737-b3c0e8c2b936",
   "metadata": {},
   "source": [
    "### Setup a Helper Function to Create a Scale Bar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "cfee0ba6-94b8-46fd-af6a-4cd33749dc68",
   "metadata": {},
   "outputs": [],
   "source": [
    "def gc_latlon_bear_dist(lat1, lon1, bear, dist):\n",
    "    \"\"\"\n",
    "    Input lat1/lon1 as decimal degrees, as well as bearing and distance from\n",
    "    the coordinate. Returns lat2/lon2 of final destination. Cannot be\n",
    "    vectorized due to atan2.\n",
    "    \"\"\"\n",
    "    re = 6371.1  # km\n",
    "    lat1r = np.deg2rad(lat1)\n",
    "    lon1r = np.deg2rad(lon1)\n",
    "    bearr = np.deg2rad(bear)\n",
    "    lat2r = np.arcsin(\n",
    "        (np.sin(lat1r) * np.cos(dist / re))\n",
    "        + (np.cos(lat1r) * np.sin(dist / re) * np.cos(bearr))\n",
    "    )\n",
    "    lon2r = lon1r + atan2(\n",
    "        np.sin(bearr) * np.sin(dist / re) * np.cos(lat1r),\n",
    "        np.cos(dist / re) - np.sin(lat1r) * np.sin(lat2r),\n",
    "    )\n",
    "    return np.rad2deg(lat2r), np.rad2deg(lon2r)\n",
    "\n",
    "\n",
    "def add_scale_line(\n",
    "    scale, ax, projection, color=\"k\", linewidth=None, fontsize=None, fontweight=None\n",
    "):\n",
    "    \"\"\"\n",
    "    Adds a line that shows the map scale in km. The line will automatically\n",
    "    scale based on zoom level of the map. Works with cartopy.\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    scale : scalar\n",
    "        Length of line to draw, in km.\n",
    "    ax : matplotlib.pyplot.Axes instance\n",
    "        Axes instance to draw line on. It is assumed that this was created\n",
    "        with a map projection.\n",
    "    projection : cartopy.crs projection\n",
    "        Cartopy projection being used in the plot.\n",
    "\n",
    "    Other Parameters\n",
    "    ----------------\n",
    "    color : str\n",
    "        Color of line and text to draw. Default is black.\n",
    "    \"\"\"\n",
    "    frac_lat = 0.15  # distance fraction from bottom of plot\n",
    "    frac_lon = 0.5  # distance fraction from left of plot\n",
    "    e1 = ax.get_extent()\n",
    "    center_lon = e1[0] + frac_lon * (e1[1] - e1[0])\n",
    "    center_lat = e1[2] + frac_lat * (e1[3] - e1[2])\n",
    "    # Main line\n",
    "    lat1, lon1 = gc_latlon_bear_dist(\n",
    "        center_lat, center_lon, -90, scale / 2.0\n",
    "    )  # left point\n",
    "    lat2, lon2 = gc_latlon_bear_dist(\n",
    "        center_lat, center_lon, 90, scale / 2.0\n",
    "    )  # right point\n",
    "    if lon1 <= e1[0] or lon2 >= e1[1]:\n",
    "        warnings.warn(\n",
    "            \"Scale line longer than extent of plot! \"\n",
    "            + \"Try shortening for best effect.\"\n",
    "        )\n",
    "    ax.plot(\n",
    "        [lon1, lon2],\n",
    "        [lat1, lat2],\n",
    "        linestyle=\"-\",\n",
    "        color=color,\n",
    "        transform=projection,\n",
    "        linewidth=linewidth,\n",
    "    )\n",
    "    # Draw a vertical hash on the left edge\n",
    "    lat1a, lon1a = gc_latlon_bear_dist(\n",
    "        lat1, lon1, 180, frac_lon * scale / 20.0\n",
    "    )  # bottom left hash\n",
    "    lat1b, lon1b = gc_latlon_bear_dist(\n",
    "        lat1, lon1, 0, frac_lon * scale / 20.0\n",
    "    )  # top left hash\n",
    "    ax.plot(\n",
    "        [lon1a, lon1b],\n",
    "        [lat1a, lat1b],\n",
    "        linestyle=\"-\",\n",
    "        color=color,\n",
    "        transform=projection,\n",
    "        linewidth=linewidth,\n",
    "    )\n",
    "    # Draw a vertical hash on the right edge\n",
    "    lat2a, lon2a = gc_latlon_bear_dist(\n",
    "        lat2, lon2, 180, frac_lon * scale / 20.0\n",
    "    )  # bottom right hash\n",
    "    lat2b, lon2b = gc_latlon_bear_dist(\n",
    "        lat2, lon2, 0, frac_lon * scale / 20.0\n",
    "    )  # top right hash\n",
    "    ax.plot(\n",
    "        [lon2a, lon2b],\n",
    "        [lat2a, lat2b],\n",
    "        linestyle=\"-\",\n",
    "        color=color,\n",
    "        transform=projection,\n",
    "        linewidth=linewidth,\n",
    "    )\n",
    "    # Draw scale label\n",
    "    ax.text(\n",
    "        center_lon,\n",
    "        center_lat - frac_lat * (e1[3] - e1[2]) / 4.0,\n",
    "        str(int(scale)) + \" km\",\n",
    "        horizontalalignment=\"center\",\n",
    "        verticalalignment=\"center\",\n",
    "        color=color,\n",
    "        fontweight=fontweight,\n",
    "        fontsize=fontsize,\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "eeac4ca0-7124-42de-a010-40939c086536",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on KMKX20210907_150152_V06\n",
      "working on KMKX20210907_150642_V06\n",
      "working on KMKX20210907_151132_V06\n",
      "working on KMKX20210907_151622_V06\n",
      "working on KMKX20210907_152121_V06\n",
      "working on KMKX20210907_152621_V06\n",
      "working on KMKX20210907_153134_V06\n",
      "working on KMKX20210907_153610_V06\n",
      "working on KMKX20210907_154205_V06\n",
      "working on KMKX20210907_154814_V06\n",
      "working on KMKX20210907_155424_V06\n",
      "working on KMKX20210907_160034_V06\n",
      "working on KMKX20210907_160607_V06\n",
      "working on KMKX20210907_161141_V06\n",
      "working on KMKX20210907_161714_V06\n",
      "working on KMKX20210907_162247_V06\n",
      "working on KMKX20210907_162924_V06\n",
      "working on KMKX20210907_163532_V06\n",
      "working on KMKX20210907_164149_V06\n",
      "working on KMKX20210907_164816_V06\n",
      "working on KMKX20210907_165433_V06\n",
      "working on KMKX20210907_170101_V06\n",
      "working on KMKX20210907_170739_V06\n",
      "working on KMKX20210907_171431_V06\n",
      "working on KMKX20210907_172123_V06\n",
      "working on KMKX20210907_172814_V06\n",
      "working on KMKX20210907_173452_V06\n",
      "working on KMKX20210907_174130_V06\n",
      "working on KMKX20210907_174807_V06\n",
      "working on KMKX20210907_175459_V06\n",
      "working on KMKX20210907_180150_V06\n",
      "working on KMKX20210907_180841_V06\n",
      "working on KMKX20210907_181448_V06\n",
      "working on KMKX20210907_182057_V06\n",
      "working on KMKX20210907_182749_V06\n",
      "working on KMKX20210907_183440_V06\n",
      "working on KMKX20210907_184048_V06\n",
      "working on KMKX20210907_184739_V06\n",
      "working on KMKX20210907_185431_V06\n",
      "working on KMKX20210907_190109_V06\n",
      "working on KMKX20210907_190703_V06\n",
      "working on KMKX20210907_191327_V06\n",
      "working on KMKX20210907_191951_V06\n",
      "working on KMKX20210907_192614_V06\n",
      "working on KMKX20210907_193238_V06\n",
      "working on KMKX20210907_193849_V06\n",
      "working on KMKX20210907_194459_V06\n",
      "working on KMKX20210907_195056_V06\n",
      "working on KMKX20210907_195642_V06\n"
     ]
    }
   ],
   "source": [
    "for i, scan in enumerate(results.iter_success(), start=1):\n",
    "    ## skip the files ending in \"MDM\"\n",
    "    if scan.filename[-3:] != \"MDM\":\n",
    "        print(\"working on \" + scan.filename)\n",
    "\n",
    "        this_time = pd.to_datetime(\n",
    "            scan.filename[4:17], format=\"%Y%m%d_%H%M\"\n",
    "        ).tz_localize(\"UTC\")\n",
    "\n",
    "        radar = scan.open_pyart()\n",
    "        # display = pyart.graph.RadarDisplay(radar)\n",
    "\n",
    "        fig = plt.figure(figsize=[15, 7])\n",
    "\n",
    "        map_panel_axes = [0.05, 0.05, 0.4, 0.80]\n",
    "        x_cut_panel_axes = [0.55, 0.10, 0.4, 0.25]\n",
    "        y_cut_panel_axes = [0.55, 0.50, 0.4, 0.25]\n",
    "\n",
    "        projection = ccrs.PlateCarree()\n",
    "\n",
    "        ## apply gatefilter (see here: https://arm-doe.github.io/pyart/notebooks/masking_data_with_gatefilters.html)\n",
    "        # gatefilter = pyart.correct.moment_based_gate_filter(radar)\n",
    "        gatefilter = pyart.filters.GateFilter(radar)\n",
    "\n",
    "        # Lets remove reflectivity values below a threshold.\n",
    "        gatefilter.exclude_below(\"reflectivity\", -2.5)\n",
    "\n",
    "        display = pyart.graph.RadarMapDisplay(radar)\n",
    "\n",
    "        ### set up plot\n",
    "        ax1 = fig.add_axes(map_panel_axes, projection=projection)\n",
    "\n",
    "        # Add some various map elements to the plot to make it recognizable.\n",
    "        ax1.add_feature(USCOUNTIES.with_scale(\"500k\"), edgecolor=\"gray\", linewidth=0.4)\n",
    "        ax1.add_feature(cfeature.STATES.with_scale(\"10m\"), linewidth=3.0)\n",
    "\n",
    "        cf = display.plot_ppi_map(\n",
    "            \"reflectivity\",\n",
    "            0,\n",
    "            vmin=-20,\n",
    "            vmax=70,\n",
    "            ax=ax1,\n",
    "            min_lon=min_lon,\n",
    "            max_lon=max_lon,\n",
    "            min_lat=min_lat,\n",
    "            max_lat=max_lat,\n",
    "            title=radar_id\n",
    "            + \" Reflectivity and Severe Weather Reports, \"\n",
    "            + this_time.strftime(\"%H%M UTC %d %b %Y\"),\n",
    "            projection=projection,\n",
    "            resolution=\"10m\",\n",
    "            gatefilter=gatefilter,\n",
    "            cmap=\"pyart_ChaseSpectral\",\n",
    "            colorbar_flag=False,\n",
    "            lat_lines=[0, 0],\n",
    "            lon_lines=[0, 0],\n",
    "        )\n",
    "\n",
    "        ## plot horizontal colorbar\n",
    "        display.plot_colorbar(cf, orient=\"horizontal\", pad=0.07)\n",
    "\n",
    "        # Plot range rings if desired\n",
    "        # display.plot_range_ring(25., color='gray', linestyle='dashed')\n",
    "        # display.plot_range_ring(50., color='gray', linestyle='dashed')\n",
    "        # display.plot_range_ring(100., color='gray', linestyle='dashed')\n",
    "\n",
    "        ax1.set_xticks(np.arange(min_lon, max_lon, 0.5), crs=ccrs.PlateCarree())\n",
    "        ax1.set_yticks(np.arange(min_lat, max_lat, 0.5), crs=ccrs.PlateCarree())\n",
    "\n",
    "        ## add marker points for severe reports\n",
    "        wind_reports_now = wind_reports[\n",
    "            (\n",
    "                (start - pd.Timedelta(minutes=30)).strftime(\"%Y-%m-%d %H:%M\")\n",
    "            ) : this_time.strftime(\"%Y-%m-%d %H:%M\")\n",
    "        ]\n",
    "        ax1.scatter(\n",
    "            wind_reports_now.slon.values.tolist(),\n",
    "            wind_reports_now.slat.values.tolist(),\n",
    "            s=20,\n",
    "            facecolors=\"none\",\n",
    "            edgecolors=\"deepskyblue\",\n",
    "            linewidths=1.8,\n",
    "            label=\"Wind Reports\",\n",
    "        )\n",
    "        tornado_reports_now = tornado_reports[\n",
    "            (\n",
    "                (start - pd.Timedelta(minutes=30)).strftime(\"%Y-%m-%d %H:%M\")\n",
    "            ) : this_time.strftime(\"%Y-%m-%d %H:%M\")\n",
    "        ]\n",
    "        ax1.scatter(\n",
    "            tornado_reports_now.slon.values.tolist(),\n",
    "            tornado_reports_now.slat.values.tolist(),\n",
    "            s=20,\n",
    "            facecolors=\"tab:red\",\n",
    "            edgecolors=\"black\",\n",
    "            marker=\"v\",\n",
    "            linewidths=1.5,\n",
    "            label=\"Tornado Reports\",\n",
    "        )\n",
    "        hail_reports_now = hail_reports[\n",
    "            (\n",
    "                (start - pd.Timedelta(minutes=30)).strftime(\"%Y-%m-%d %H:%M\")\n",
    "            ) : this_time.strftime(\"%Y-%m-%d %H:%M\")\n",
    "        ]\n",
    "        ax1.scatter(\n",
    "            hail_reports_now.slon.values.tolist(),\n",
    "            hail_reports_now.slat.values.tolist(),\n",
    "            s=20,\n",
    "            facecolors=\"none\",\n",
    "            edgecolors=\"lawngreen\",\n",
    "            linewidths=1.8,\n",
    "            label=\"Hail Reports\",\n",
    "        )\n",
    "        plt.legend(loc=\"upper right\")\n",
    "\n",
    "        add_scale_line(\n",
    "            100.0,\n",
    "            ax1,\n",
    "            projection=ccrs.PlateCarree(),\n",
    "            color=\"black\",\n",
    "            linewidth=3,\n",
    "            fontsize=18,\n",
    "        )\n",
    "\n",
    "        plt.savefig(\n",
    "            scan.radar_id + \"_\" + scan.filename[4:17] + \"_dz_rpts.png\",\n",
    "            bbox_inches=\"tight\",\n",
    "            dpi=300,\n",
    "            facecolor=\"white\",\n",
    "            transparent=False,\n",
    "        )\n",
    "        # plt.show()\n",
    "        plt.close(\"all\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c037a118-73c3-4163-aa0f-4dde5bc8b07b",
   "metadata": {},
   "source": [
    "### Create an Animation of the Images\n",
    "We use the `imageio` library to create an animation of the images (an mp4 file)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "70ef90d2-744a-4ffd-99f3-b219d8bc2b7d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IMAGEIO FFMPEG_WRITER WARNING: input image is not divisible by macro_block_size=16, resizing from (1930, 1766) to (1936, 1776) to ensure video compatibility with most codecs and players. To prevent resizing, make your input image divisible by the macro_block_size or set the macro_block_size to 1 (risking incompatibility).\n"
     ]
    }
   ],
   "source": [
    "map_images = sorted(glob.glob(f\"{radar_id}*\"))\n",
    "gif_title = f\"{radar_id}-map-animation.mp4\"\n",
    "\n",
    "# Check to see if the file exists - if it does, delete it\n",
    "if os.path.exists(gif_title):\n",
    "    os.remove(gif_title)\n",
    "\n",
    "# Loop through and create the gif\n",
    "with imageio.get_writer(gif_title, fps=5) as writer:\n",
    "    for filename in map_images:\n",
    "        image = imageio.imread(filename)\n",
    "        writer.append_data(image)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7cfbd4b-4533-4fc9-bbe8-c5c2d3741bca",
   "metadata": {},
   "source": [
    "## View the Final Animation\n",
    "Now that we have our images and animation, let's view the file!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "e72998e4-18f3-43dc-9641-002295bf2b55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<video src=\"KMKX-map-animation.mp4\" controls  width=\"500\" >\n",
       "      Your browser does not support the <code>video</code> element.\n",
       "    </video>"
      ],
      "text/plain": [
       "<IPython.core.display.Video object>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Video\n",
    "\n",
    "Video(gif_title, width=500)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "824f8454-fb8f-427c-9d10-4264e7212fe6",
   "metadata": {},
   "source": [
    "## Conclusion\n",
    "Within this post, we detailed how to go about combining multiple data sources from the cloud-hosted NEXRAD archive and the SPC report archive. We created a detailed map of key fields, along with the report locations, and created an animation.\n",
    "\n",
    "These sorts of visualizations can be helpful when creating event overviews, or retrospectives!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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 "metadata": {
  "author": "Max Grover,Russ Schumacher",
  "date": "2022-11-23",
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  "title": "Hail Storm Visualization Using Py-ART and Pandas!",
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