kmuehlbauer/analyze_dwd_grids.ipynb

## analyze_dwd_grids.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import wradlib as wrl\n",
    "import matplotlib.pyplot as pl\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "from osgeo import osr\n",
    "import cartopy.crs as ccrs\n",
    "import pint_xarray"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PROJCS[\"Radolan Projection\",\n",
      "    GEOGCS[\"Radolan Coordinate System\",\n",
      "        DATUM[\"Radolan_Kugel\",\n",
      "            SPHEROID[\"Erdkugel\",6370040,0]],\n",
      "        PRIMEM[\"Greenwich\",0,\n",
      "            AUTHORITY[\"EPSG\",\"8901\"]],\n",
      "        UNIT[\"degree\",0.0174532925199433,\n",
      "            AUTHORITY[\"EPSG\",\"9122\"]]],\n",
      "    PROJECTION[\"Polar_Stereographic\"],\n",
      "    PARAMETER[\"latitude_of_origin\",60],\n",
      "    PARAMETER[\"central_meridian\",10],\n",
      "    PARAMETER[\"false_easting\",0],\n",
      "    PARAMETER[\"false_northing\",0],\n",
      "    UNIT[\"kilometre\",1000,\n",
      "        AUTHORITY[\"EPSG\",\"9036\"]],\n",
      "    AXIS[\"Easting\",SOUTH],\n",
      "    AXIS[\"Northing\",SOUTH]]\n"
     ]
    }
   ],
   "source": [
    "p_legacy = wrl.georef.create_osr(\"dwd-radolan\")\n",
    "print(p_legacy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PROJCS[\"Radolan Projection\",\n",
      "    GEOGCS[\"Radolan Coordinate System\",\n",
      "        DATUM[\"Radolan_Kugel\",\n",
      "            SPHEROID[\"Erdkugel\",6370040,0]],\n",
      "        PRIMEM[\"Greenwich\",0,\n",
      "            AUTHORITY[\"EPSG\",\"8901\"]],\n",
      "        UNIT[\"degree\",0.0174532925199433,\n",
      "            AUTHORITY[\"EPSG\",\"9122\"]]],\n",
      "    PROJECTION[\"Polar_Stereographic\"],\n",
      "    PARAMETER[\"latitude_of_origin\",60],\n",
      "    PARAMETER[\"central_meridian\",10],\n",
      "    PARAMETER[\"false_easting\",0],\n",
      "    PARAMETER[\"false_northing\",0],\n",
      "    UNIT[\"metre\",1,\n",
      "        AUTHORITY[\"EPSG\",\"9001\"]],\n",
      "    AXIS[\"Easting\",SOUTH],\n",
      "    AXIS[\"Northing\",SOUTH]]\n"
     ]
    }
   ],
   "source": [
    "p_legacy_sphere = wrl.georef.create_osr(\"dwd-radolan-sphere\")\n",
    "print(p_legacy_sphere)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PROJCS[\"Radolan Projection\",\n",
      "    GEOGCS[\"Radolan Coordinate System\",\n",
      "        DATUM[\"unknown based on WGS 84\",\n",
      "            SPHEROID[\"WGS 84\",6378137,298.25722356301]],\n",
      "        PRIMEM[\"Greenwich\",0,\n",
      "            AUTHORITY[\"EPSG\",\"8901\"]],\n",
      "        UNIT[\"degree\",0.0174532925199433,\n",
      "            AUTHORITY[\"EPSG\",\"9122\"]]],\n",
      "    PROJECTION[\"Polar_Stereographic\"],\n",
      "    PARAMETER[\"latitude_of_origin\",60],\n",
      "    PARAMETER[\"central_meridian\",10],\n",
      "    PARAMETER[\"false_easting\",0],\n",
      "    PARAMETER[\"false_northing\",0],\n",
      "    UNIT[\"metre\",1,\n",
      "        AUTHORITY[\"EPSG\",\"9001\"]],\n",
      "    AXIS[\"Easting\",SOUTH],\n",
      "    AXIS[\"Northing\",SOUTH]]\n"
     ]
    }
   ],
   "source": [
    "p_legacy_wgs84 = wrl.georef.create_osr(\"dwd-radolan-wgs84\")\n",
    "print(p_legacy_wgs84)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PROJCS[\"Radolan Projection\",\n",
      "    GEOGCS[\"Radolan Coordinate System\",\n",
      "        DATUM[\"Radolan_Kugel\",\n",
      "            SPHEROID[\"Erdkugel\",6370040,0]],\n",
      "        PRIMEM[\"Greenwich\",0,\n",
      "            AUTHORITY[\"EPSG\",\"8901\"]],\n",
      "        UNIT[\"degree\",0.0174532925199433,\n",
      "            AUTHORITY[\"EPSG\",\"9122\"]]],\n",
      "    PROJECTION[\"Polar_Stereographic\"],\n",
      "    PARAMETER[\"latitude_of_origin\",60],\n",
      "    PARAMETER[\"central_meridian\",10],\n",
      "    PARAMETER[\"false_easting\",522962.166921856],\n",
      "    PARAMETER[\"false_northing\",3759144.72426557],\n",
      "    UNIT[\"metre\",1,\n",
      "        AUTHORITY[\"EPSG\",\"9001\"]],\n",
      "    AXIS[\"Easting\",SOUTH],\n",
      "    AXIS[\"Northing\",SOUTH]]\n",
      "PROJCS[\"Radolan Projection\",\n",
      "    GEOGCS[\"Radolan Coordinate System\",\n",
      "        DATUM[\"unknown based on WGS 84\",\n",
      "            SPHEROID[\"WGS 84\",6378137,298.25722356301]],\n",
      "        PRIMEM[\"Greenwich\",0,\n",
      "            AUTHORITY[\"EPSG\",\"8901\"]],\n",
      "        UNIT[\"degree\",0.0174532925199433,\n",
      "            AUTHORITY[\"EPSG\",\"9122\"]]],\n",
      "    PROJECTION[\"Polar_Stereographic\"],\n",
      "    PARAMETER[\"latitude_of_origin\",60],\n",
      "    PARAMETER[\"central_meridian\",10],\n",
      "    PARAMETER[\"false_easting\",523196.835217778],\n",
      "    PARAMETER[\"false_northing\",3772588.86193113],\n",
      "    UNIT[\"metre\",1,\n",
      "        AUTHORITY[\"EPSG\",\"9001\"]],\n",
      "    AXIS[\"Easting\",SOUTH],\n",
      "    AXIS[\"Northing\",SOUTH]]\n"
     ]
    }
   ],
   "source": [
    "p_rx_sphere = wrl.georef.create_osr(\"dwd-radolan-sphere-rx\")\n",
    "p_rx_wgs84 = wrl.georef.create_osr(\"dwd-radolan-wgs84-rx\")\n",
    "print(p_rx_sphere)\n",
    "print(p_rx_wgs84)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PROJCS[\"Radolan Projection\",\n",
      "    GEOGCS[\"Radolan Coordinate System\",\n",
      "        DATUM[\"Radolan_Kugel\",\n",
      "            SPHEROID[\"Erdkugel\",6370040,0]],\n",
      "        PRIMEM[\"Greenwich\",0,\n",
      "            AUTHORITY[\"EPSG\",\"8901\"]],\n",
      "        UNIT[\"degree\",0.0174532925199433,\n",
      "            AUTHORITY[\"EPSG\",\"9122\"]]],\n",
      "    PROJECTION[\"Polar_Stereographic\"],\n",
      "    PARAMETER[\"latitude_of_origin\",60],\n",
      "    PARAMETER[\"central_meridian\",10],\n",
      "    PARAMETER[\"false_easting\",542962.166921857],\n",
      "    PARAMETER[\"false_northing\",3609144.72426557],\n",
      "    UNIT[\"metre\",1,\n",
      "        AUTHORITY[\"EPSG\",\"9001\"]],\n",
      "    AXIS[\"Easting\",SOUTH],\n",
      "    AXIS[\"Northing\",SOUTH]]\n",
      "PROJCS[\"Radolan Projection\",\n",
      "    GEOGCS[\"Radolan Coordinate System\",\n",
      "        DATUM[\"unknown based on WGS 84\",\n",
      "            SPHEROID[\"WGS 84\",6378137,298.25722356301]],\n",
      "        PRIMEM[\"Greenwich\",0,\n",
      "            AUTHORITY[\"EPSG\",\"8901\"]],\n",
      "        UNIT[\"degree\",0.0174532925199433,\n",
      "            AUTHORITY[\"EPSG\",\"9122\"]]],\n",
      "    PROJECTION[\"Polar_Stereographic\"],\n",
      "    PARAMETER[\"latitude_of_origin\",60],\n",
      "    PARAMETER[\"central_meridian\",10],\n",
      "    PARAMETER[\"false_easting\",543196.835217764],\n",
      "    PARAMETER[\"false_northing\",3622588.861931],\n",
      "    UNIT[\"metre\",1,\n",
      "        AUTHORITY[\"EPSG\",\"9001\"]],\n",
      "    AXIS[\"Easting\",SOUTH],\n",
      "    AXIS[\"Northing\",SOUTH]]\n"
     ]
    }
   ],
   "source": [
    "p_de1200_sphere = wrl.georef.create_osr(\"dwd-radolan-sphere-de1200\")\n",
    "p_de1200_wgs84 = wrl.georef.create_osr(\"dwd-radolan-wgs84-de1200\")\n",
    "print(p_de1200_sphere)\n",
    "print(p_de1200_wgs84)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PROJCS[\"Radolan Projection\",\n",
      "    GEOGCS[\"Radolan Coordinate System\",\n",
      "        DATUM[\"Radolan_Kugel\",\n",
      "            SPHEROID[\"Erdkugel\",6370040,0]],\n",
      "        PRIMEM[\"Greenwich\",0,\n",
      "            AUTHORITY[\"EPSG\",\"8901\"]],\n",
      "        UNIT[\"degree\",0.0174532925199433,\n",
      "            AUTHORITY[\"EPSG\",\"9122\"]]],\n",
      "    PROJECTION[\"Polar_Stereographic\"],\n",
      "    PARAMETER[\"latitude_of_origin\",60],\n",
      "    PARAMETER[\"central_meridian\",10],\n",
      "    PARAMETER[\"false_easting\",543337.166921856],\n",
      "    PARAMETER[\"false_northing\",3608769.72426557],\n",
      "    UNIT[\"metre\",1,\n",
      "        AUTHORITY[\"EPSG\",\"9001\"]],\n",
      "    AXIS[\"Easting\",SOUTH],\n",
      "    AXIS[\"Northing\",SOUTH]]\n",
      "PROJCS[\"Radolan Projection\",\n",
      "    GEOGCS[\"Radolan Coordinate System\",\n",
      "        DATUM[\"unknown based on WGS 84\",\n",
      "            SPHEROID[\"WGS 84\",6378137,298.25722356301]],\n",
      "        PRIMEM[\"Greenwich\",0,\n",
      "            AUTHORITY[\"EPSG\",\"8901\"]],\n",
      "        UNIT[\"degree\",0.0174532925199433,\n",
      "            AUTHORITY[\"EPSG\",\"9122\"]]],\n",
      "    PROJECTION[\"Polar_Stereographic\"],\n",
      "    PARAMETER[\"latitude_of_origin\",60],\n",
      "    PARAMETER[\"central_meridian\",10],\n",
      "    PARAMETER[\"false_easting\",543571.835217764],\n",
      "    PARAMETER[\"false_northing\",3622213.861931],\n",
      "    UNIT[\"metre\",1,\n",
      "        AUTHORITY[\"EPSG\",\"9001\"]],\n",
      "    AXIS[\"Easting\",SOUTH],\n",
      "    AXIS[\"Northing\",SOUTH]]\n"
     ]
    }
   ],
   "source": [
    "p_de4800_sphere = wrl.georef.create_osr(\"dwd-radolan-sphere-de4800\")\n",
    "p_de4800_wgs84 = wrl.georef.create_osr(\"dwd-radolan-wgs84-de4800\")\n",
    "print(p_de4800_sphere)\n",
    "print(p_de4800_wgs84)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "469500.0000000011 -599499.9999999991\n",
      "(array(469500.), array(-599500.))\n",
      "(array(469500.00000006), array(-599499.99999959))\n"
     ]
    }
   ],
   "source": [
    "xy = wrl.georef.get_radolan_coords(9.0, 51.0, proj=p_legacy)\n",
    "print(xy[0] * 1000 + 542962.166921857, xy[1] * 1000 + 3609144.7242655745 )\n",
    "print(wrl.georef.get_radolan_coords(9.0, 51.0, proj=p_de1200_sphere))\n",
    "print(wrl.georef.get_radolan_coords(9.0, 51.0, proj=p_de1200_wgs84))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get Coordinates and Grids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 49.6 ms, sys: 8.46 ms, total: 58.1 ms\n",
      "Wall time: 56.2 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "mode=\"center\"\n",
    "radolan_coords = wrl.georef.get_radolan_coordinates(nrows=1200, ncols=1100, mode=\"radolan\")\n",
    "radolan_coords_rx_sphere = wrl.georef.get_radolan_coordinates(nrows=900, ncols=900, mode=mode, proj=p_rx_sphere)\n",
    "radolan_coords_rx_wgs84 = wrl.georef.get_radolan_coordinates(nrows=900, ncols=900, mode=mode, proj=p_rx_wgs84)\n",
    "radolan_coords_de1200_sphere = wrl.georef.get_radolan_coordinates(nrows=1200, ncols=1100, mode=mode, proj=p_de1200_sphere)\n",
    "radolan_coords_de1200_wgs84 = wrl.georef.get_radolan_coordinates(nrows=1200, ncols=1100, mode=mode, proj=p_de1200_wgs84)\n",
    "radolan_coords_de4800_sphere = wrl.georef.get_radolan_coordinates(nrows=4800, ncols=4400, mode=mode, proj=p_de4800_sphere)\n",
    "radolan_coords_de4800_wgs84 = wrl.georef.get_radolan_coordinates(nrows=4800, ncols=4400, mode=mode, proj=p_de4800_wgs84)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 53.1 s, sys: 3.1 s, total: 56.2 s\n",
      "Wall time: 56.1 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "wgs84=True\n",
    "mode=\"center\"\n",
    "radolan_grid = wrl.georef.get_radolan_grid(nrows=1200, ncols=1100, wgs84=wgs84, mode=\"radolan\")\n",
    "radolan_grid_rx_sphere = wrl.georef.get_radolan_grid(nrows=900, ncols=900, wgs84=wgs84, mode=mode, proj=p_rx_sphere)\n",
    "radolan_grid_rx_wgs84 = wrl.georef.get_radolan_grid(nrows=900, ncols=900, wgs84=wgs84, mode=mode, proj=p_rx_wgs84)\n",
    "radolan_grid_de1200_sphere = wrl.georef.get_radolan_grid(nrows=1200, ncols=1100, wgs84=wgs84, mode=mode, proj=p_de1200_sphere)\n",
    "radolan_grid_de1200_wgs84 = wrl.georef.get_radolan_grid(nrows=1200, ncols=1100, wgs84=wgs84, mode=mode, proj=p_de1200_wgs84)\n",
    "radolan_grid_de4800_sphere = wrl.georef.get_radolan_grid(nrows=4800, ncols=4400, wgs84=wgs84, mode=mode, proj=p_de4800_sphere)\n",
    "radolan_grid_de4800_wgs84 = wrl.georef.get_radolan_grid(nrows=4800, ncols=4400, wgs84=wgs84, mode=mode, proj=p_de4800_wgs84)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 53.9 s, sys: 3.01 s, total: 56.9 s\n",
      "Wall time: 56.8 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "mode=\"edge\"\n",
    "radolan_grid_e = wrl.georef.get_radolan_grid(nrows=1200, ncols=1100, wgs84=wgs84, mode=mode)\n",
    "radolan_grid_rx_sphere_e = wrl.georef.get_radolan_grid(nrows=900, ncols=900, wgs84=wgs84, mode=mode, proj=p_rx_sphere)\n",
    "radolan_grid_rx_wgs84_e = wrl.georef.get_radolan_grid(nrows=900, ncols=900, wgs84=wgs84, mode=mode, proj=p_rx_wgs84)\n",
    "radolan_grid_de1200_sphere_e = wrl.georef.get_radolan_grid(nrows=1200, ncols=1100, wgs84=wgs84, mode=mode, proj=p_de1200_sphere)\n",
    "radolan_grid_de1200_wgs84_e = wrl.georef.get_radolan_grid(nrows=1200, ncols=1100, wgs84=wgs84, mode=mode, proj=p_de1200_wgs84)\n",
    "radolan_grid_de4800_sphere_e = wrl.georef.get_radolan_grid(nrows=4800, ncols=4400, wgs84=wgs84, mode=mode, proj=p_de4800_sphere)\n",
    "radolan_grid_de4800_wgs84_e = wrl.georef.get_radolan_grid(nrows=4800, ncols=4400, wgs84=wgs84, mode=mode, proj=p_de4800_wgs84)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Corner Coordinates - New DWD Grid Projection Sphere RX"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NW: [ 2.07147966 54.58771052]\n",
      "NO: [15.72075586 54.74054767]\n",
      "SO: [14.6209217  47.07046581]\n",
      "SW: [ 3.58892995 46.95258041]\n"
     ]
    }
   ],
   "source": [
    "print(\"NW:\", radolan_grid_rx_sphere_e[-1, 0])\n",
    "print(\"NO:\", radolan_grid_rx_sphere_e[-1, -1])\n",
    "print(\"SO:\", radolan_grid_rx_sphere_e[0, -1])\n",
    "print(\"SW:\", radolan_grid_rx_sphere_e[0, 0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Corner Coordinates - New DWD Grid Projection WGS84 RX"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NW: [ 2.09588321 54.58546706]\n",
      "NO: [15.69697166 54.73806893]\n",
      "SO: [14.60482286 47.07156997]\n",
      "SW: [ 3.604383   46.95361533]\n"
     ]
    }
   ],
   "source": [
    "print(\"NW:\", radolan_grid_rx_wgs84_e[-1, 0])\n",
    "print(\"NO:\", radolan_grid_rx_wgs84_e[-1, -1])\n",
    "print(\"SO:\", radolan_grid_rx_wgs84_e[0, -1])\n",
    "print(\"SW:\", radolan_grid_rx_wgs84_e[0, 0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Corner Coordinates - Current DWD Grid Projection DE1200"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NW: [ 1.43561214 55.86584289]\n",
      "NO: [18.76728172 55.84848692]\n",
      "SO: [16.60186543 45.68358331]\n",
      "SW: [ 3.5519213  45.69587048]\n"
     ]
    }
   ],
   "source": [
    "print(\"NW:\", radolan_grid_e[-1, 0])\n",
    "print(\"NO:\", radolan_grid_e[-1, -1])\n",
    "print(\"SO:\", radolan_grid_e[0, -1])\n",
    "print(\"SW:\", radolan_grid_e[0, 0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Corner Coordinates - New DWD Grid Projection Sphere DE1200\n",
    "\n",
    "should be same as above"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NW: [ 1.43561214 55.86584289]\n",
      "NO: [18.76728172 55.84848692]\n",
      "SO: [16.60186543 45.68358331]\n",
      "SW: [ 3.5519213  45.69587048]\n"
     ]
    }
   ],
   "source": [
    "print(\"NW:\", radolan_grid_de1200_sphere_e[-1, 0])\n",
    "print(\"NO:\", radolan_grid_de1200_sphere_e[-1, -1])\n",
    "print(\"SO:\", radolan_grid_de1200_sphere_e[0, -1])\n",
    "print(\"SW:\", radolan_grid_de1200_sphere_e[0, 0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Corner Coordinates - New DWD Grid Projection Sphere DE4800"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NW: [ 1.43561214 55.86584289]\n",
      "NO: [18.76728172 55.84848692]\n",
      "SO: [16.60186543 45.68358331]\n",
      "SW: [ 3.5519213  45.69587048]\n"
     ]
    }
   ],
   "source": [
    "print(\"NW:\", radolan_grid_de4800_sphere_e[-1, 0])\n",
    "print(\"NO:\", radolan_grid_de4800_sphere_e[-1, -1])\n",
    "print(\"SO:\", radolan_grid_de4800_sphere_e[0, -1])\n",
    "print(\"SW:\", radolan_grid_de4800_sphere_e[0, 0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Corner Coordinates - New DWD Grid Projection WGS84 DE1200"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NW: [ 1.46330151 55.86208711]\n",
      "NO: [18.73161645 55.84543856]\n",
      "SO: [16.58086935 45.68460578]\n",
      "SW: [ 3.56699464 45.69642538]\n"
     ]
    }
   ],
   "source": [
    "print(\"NW:\", radolan_grid_de1200_wgs84_e[-1, 0])\n",
    "print(\"NO:\", radolan_grid_de1200_wgs84_e[-1, -1])\n",
    "print(\"SO:\", radolan_grid_de1200_wgs84_e[0, -1])\n",
    "print(\"SW:\", radolan_grid_de1200_wgs84_e[0, 0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Corner Coordinates - New DWD Grid Projection WGS84 DE4800"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NW: [ 1.46330151 55.86208711]\n",
      "NO: [18.73161645 55.84543856]\n",
      "SO: [16.58086935 45.68460578]\n",
      "SW: [ 3.56699464 45.69642538]\n"
     ]
    }
   ],
   "source": [
    "print(\"NW:\", radolan_grid_de4800_wgs84_e[-1, 0])\n",
    "print(\"NO:\", radolan_grid_de4800_wgs84_e[-1, -1])\n",
    "print(\"SO:\", radolan_grid_de4800_wgs84_e[0, -1])\n",
    "print(\"SW:\", radolan_grid_de4800_wgs84_e[0, 0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example Files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "WGS84_FILE = \"/home/kai/projects/data/radar_all_over_the_world/wradlib_wn_wgs84_test_reduced/wgs84/WN2204091200_000\"\n",
    "SPHERE_FILE = \"/home/kai/projects/data/radar_all_over_the_world/wradlib_wn_wgs84_test_reduced/sphere/WN2204091200_000\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/kai/mambaforge/envs/wradlib/lib/python3.10/site-packages/xarray/conventions.py:521: SerializationWarning: variable 'WN' has multiple fill values {2490, 2500, 65535}, decoding all values to NaN.\n",
      "  new_vars[k] = decode_cf_variable(\n",
      "/home/kai/mambaforge/envs/wradlib/lib/python3.10/site-packages/xarray/conventions.py:521: SerializationWarning: variable 'WN' has multiple fill values {2490, 2500, 65535}, decoding all values to NaN.\n",
      "  new_vars[k] = decode_cf_variable(\n"
     ]
    }
   ],
   "source": [
    "ds0 = xr.open_dataset(WGS84_FILE, engine=\"radolan\")\n",
    "ds1 = xr.open_dataset(SPHERE_FILE, engine=\"radolan\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# assign longlat WGS84"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (y: 1200, x: 1100, time: 1)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2022-04-09T12:00:00\n",
       "  * y        (y) float64 -4.822e+06 -4.821e+06 ... -3.624e+06 -3.623e+06\n",
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       "    x0       (x) float64 6.123e-08 1e+03 2e+03 ... 1.097e+06 1.098e+06 1.099e+06\n",
       "    y0       (y) float64 -1.199e+06 -1.198e+06 -1.197e+06 ... -1e+03 4.061e-07\n",
       "    lon      (y, x) float64 3.572 3.584 3.596 3.607 ... 18.68 18.69 18.71 18.72\n",
       "    lat      (y, x) float64 45.7 45.7 45.7 45.7 45.7 ... 55.85 55.84 55.84 55.84\n",
       "Data variables:\n",
       "    WN       (y, x) float32 ...\n",
       "Attributes:\n",
       "    radarid:         10000\n",
       "    formatversion:   5\n",
       "    radolanversion:  P300000H\n",
       "    radarlocations:  [&#x27;&#x27;]\n",
       "    predictiontime:  0\n",
       "    moduleflag:      8</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-7ff1a930-a59d-42d2-a66a-1f8107ef7f45' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7ff1a930-a59d-42d2-a66a-1f8107ef7f45' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 1200</li><li><span class='xr-has-index'>x</span>: 1100</li><li><span class='xr-has-index'>time</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8995b3c6-85c5-47bb-ae7b-55a7b2d9fd03' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8995b3c6-85c5-47bb-ae7b-55a7b2d9fd03' class='xr-section-summary' >Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-04-09T12:00:00</div><input id='attrs-9d73e131-a03a-41a7-8efe-b0ab3effc6db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9d73e131-a03a-41a7-8efe-b0ab3effc6db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e3eee85-814b-445b-ab5d-3b9d242cd4d0' class='xr-var-data-in' type='checkbox'><label for='data-8e3eee85-814b-445b-ab5d-3b9d242cd4d0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-04-09T12:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.822e+06 ... -3.623e+06</div><input id='attrs-4676cb20-d205-4c9b-8051-ebb63beeb098' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4676cb20-d205-4c9b-8051-ebb63beeb098' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8db94441-a111-4080-a1c9-2e435b7b6d26' class='xr-var-data-in' type='checkbox'><label for='data-8db94441-a111-4080-a1c9-2e435b7b6d26' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-4821588.861931, -4820588.861931, -4819588.861931, ..., -3624588.861931,\n",
       "       -3623588.861931, -3622588.861931])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.432e+05 -5.422e+05 ... 5.558e+05</div><input id='attrs-f01faa06-27bc-4544-be08-5c5866909f1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f01faa06-27bc-4544-be08-5c5866909f1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-478a2640-9984-44c5-a3a9-11b06bdd7a90' class='xr-var-data-in' type='checkbox'><label for='data-478a2640-9984-44c5-a3a9-11b06bdd7a90' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-543196.835218, -542196.835218, -541196.835218, ...,  553803.164782,\n",
       "        554803.164782,  555803.164782])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x0</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.123e-08 1e+03 ... 1.099e+06</div><input id='attrs-3fc745e5-9565-430f-bcab-3bd69cb5e33b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3fc745e5-9565-430f-bcab-3bd69cb5e33b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da408d90-caaa-4d05-a926-7c4f41860fc8' class='xr-var-data-in' type='checkbox'><label for='data-da408d90-caaa-4d05-a926-7c4f41860fc8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6.12344593e-08, 1.00000000e+03, 2.00000000e+03, ...,\n",
       "       1.09700000e+06, 1.09800000e+06, 1.09900000e+06])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y0</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.199e+06 -1.198e+06 ... 4.061e-07</div><input id='attrs-24d03ba5-2915-43e3-803d-fcdee56964a0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-24d03ba5-2915-43e3-803d-fcdee56964a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-598c7d85-9212-416a-ae3b-33012b9eccb5' class='xr-var-data-in' type='checkbox'><label for='data-598c7d85-9212-416a-ae3b-33012b9eccb5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-1.19900000e+06, -1.19800000e+06, -1.19700000e+06, ...,\n",
       "       -2.00000000e+03, -1.00000000e+03,  4.06056643e-07])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.572 3.584 3.596 ... 18.71 18.72</div><input id='attrs-9d1bbd2f-4202-4f3b-8190-72037401c94f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9d1bbd2f-4202-4f3b-8190-72037401c94f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0bfbd3ae-d246-4f04-8f81-d2a6ac31df62' class='xr-var-data-in' type='checkbox'><label for='data-0bfbd3ae-d246-4f04-8f81-d2a6ac31df62' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 3.57220018,  3.58393469,  3.59566974, ..., 16.55222641,\n",
       "        16.56395458, 16.5756822 ],\n",
       "       [ 3.57087793,  3.58261482,  3.59435225, ..., 16.55357381,\n",
       "        16.56530434, 16.57703433],\n",
       "       [ 3.56955515,  3.58129441,  3.59303421, ..., 16.55492175,\n",
       "        16.56665466, 16.57838702],\n",
       "       ...,\n",
       "       [ 1.47683288,  1.49229381,  1.50775598, ..., 18.68707338,\n",
       "        18.70251966, 18.71796466],\n",
       "       [ 1.47451531,  1.48998031,  1.50544656, ..., 18.68943416,\n",
       "        18.7048845 , 18.72033358],\n",
       "       [ 1.47219648,  1.48766557,  1.5031359 , ..., 18.69179621,\n",
       "        18.70725063, 18.72270377]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>45.7 45.7 45.7 ... 55.84 55.84</div><input id='attrs-d8042d35-5354-4ea7-80d0-5e638bd1ccfd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d8042d35-5354-4ea7-80d0-5e638bd1ccfd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7896476-16e7-408e-810e-b2f6ce5cd0a2' class='xr-var-data-in' type='checkbox'><label for='data-f7896476-16e7-408e-810e-b2f6ce5cd0a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[45.70099971, 45.70192517, 45.70284896, ..., 45.69108067,\n",
       "        45.69013574, 45.68918914],\n",
       "       [45.7092221 , 45.7101478 , 45.71107183, ..., 45.69930047,\n",
       "        45.69835529, 45.69740844],\n",
       "       [45.71744493, 45.71837088, 45.71929515, ..., 45.70752071,\n",
       "        45.70657528, 45.70562818],\n",
       "       ...,\n",
       "       [55.84099053, 55.84229307, 55.84359328, ..., 55.82703147,\n",
       "        55.82570181, 55.82436981],\n",
       "       [55.84968997, 55.85099292, 55.85229354, ..., 55.83572652,\n",
       "        55.83439644, 55.83306402],\n",
       "       [55.85838975, 55.85969311, 55.86099414, ..., 55.8444219 ,\n",
       "        55.8430914 , 55.84175856]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-30003ec7-58a9-4ea4-b7a2-5ebbaa491628' class='xr-section-summary-in' type='checkbox'  checked><label for='section-30003ec7-58a9-4ea4-b7a2-5ebbaa491628' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>WN</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-df3db1d6-89b2-43c9-88f0-74039206df25' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-df3db1d6-89b2-43c9-88f0-74039206df25' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cdfca88c-78c7-482c-8f97-3448c0cb3027' class='xr-var-data-in' type='checkbox'><label for='data-cdfca88c-78c7-482c-8f97-3448c0cb3027' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>4095</dd><dt><span>standard_name :</span></dt><dd>equivalent_reflectivity_factor</dd><dt><span>long_name :</span></dt><dd>WN</dd><dt><span>unit :</span></dt><dd>dBZ</dd></dl></div><div class='xr-var-data'><pre>[1320000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1b683ecf-6da6-4648-bdb6-4d9a794e1231' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1b683ecf-6da6-4648-bdb6-4d9a794e1231' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>radarid :</span></dt><dd>10000</dd><dt><span>formatversion :</span></dt><dd>5</dd><dt><span>radolanversion :</span></dt><dd>P300000H</dd><dt><span>radarlocations :</span></dt><dd>[&#x27;&#x27;]</dd><dt><span>predictiontime :</span></dt><dd>0</dd><dt><span>moduleflag :</span></dt><dd>8</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (y: 1200, x: 1100, time: 1)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2022-04-09T12:00:00\n",
       "  * y        (y) float64 -4.822e+06 -4.821e+06 ... -3.624e+06 -3.623e+06\n",
       "  * x        (x) float64 -5.432e+05 -5.422e+05 ... 5.548e+05 5.558e+05\n",
       "    x0       (x) float64 6.123e-08 1e+03 2e+03 ... 1.097e+06 1.098e+06 1.099e+06\n",
       "    y0       (y) float64 -1.199e+06 -1.198e+06 -1.197e+06 ... -1e+03 4.061e-07\n",
       "    lon      (y, x) float64 3.572 3.584 3.596 3.607 ... 18.68 18.69 18.71 18.72\n",
       "    lat      (y, x) float64 45.7 45.7 45.7 45.7 45.7 ... 55.85 55.84 55.84 55.84\n",
       "Data variables:\n",
       "    WN       (y, x) float32 ...\n",
       "Attributes:\n",
       "    radarid:         10000\n",
       "    formatversion:   5\n",
       "    radolanversion:  P300000H\n",
       "    radarlocations:  ['']\n",
       "    predictiontime:  0\n",
       "    moduleflag:      8"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds0 = ds0.assign_coords({\"x0\": ([\"x\"], radolan_coords_de1200_wgs84[0]),\n",
    "                         \"y0\": ([\"y\"], radolan_coords_de1200_wgs84[1]),\n",
    "                         \"lon\": ([\"y\", \"x\"], radolan_grid_de1200_wgs84[..., 0]),\n",
    "                         \"lat\": ([\"y\", \"x\"], radolan_grid_de1200_wgs84[..., 1])})\n",
    "ds0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# center points of corner grid cells"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NW: 1.4721964849605242 55.858389752371586\n",
      "NO: 18.72270376998116 55.84175856409139\n",
      "SO: 16.57568219837202 45.68918913521031\n",
      "SW: 3.572200176974152 45.700999706354196\n"
     ]
    }
   ],
   "source": [
    "print(\"NW:\", ds0.lon[-1, 0].values, ds0.lat[-1, 0].values)\n",
    "print(\"NO:\", ds0.lon[-1, -1].values, ds0.lat[-1, -1].values)\n",
    "print(\"SO:\", ds0.lon[0, -1].values, ds0.lat[0, -1].values)\n",
    "print(\"SW:\", ds0.lon[0, 0].values, ds0.lat[0, 0].values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visalization WGS84"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f015a5ad540>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds0.WN.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f015a4e0160>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds0.WN.plot(x=\"x0\", y=\"y0\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# assign longlat Sphere"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (y: 1200, x: 1100, time: 1)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2022-04-09T12:00:00\n",
       "  * y        (y) float64 -4.808e+06 -4.807e+06 ... -3.61e+06 -3.609e+06\n",
       "  * x        (x) float64 -5.43e+05 -5.42e+05 -5.41e+05 ... 5.55e+05 5.56e+05\n",
       "    x0       (x) float64 1.106e-09 1e+03 2e+03 ... 1.097e+06 1.098e+06 1.099e+06\n",
       "    y0       (y) float64 -1.199e+06 -1.198e+06 -1.197e+06 ... -1e+03 -2.794e-09\n",
       "    lon      (y, x) float64 3.557 3.569 3.581 3.592 ... 18.71 18.73 18.74 18.76\n",
       "    lat      (y, x) float64 45.7 45.7 45.7 45.7 45.7 ... 55.85 55.85 55.85 55.84\n",
       "Data variables:\n",
       "    WN       (y, x) float32 ...\n",
       "Attributes:\n",
       "    radarid:         10000\n",
       "    formatversion:   3\n",
       "    radolanversion:  P300003H\n",
       "    radarlocations:  [&#x27;&#x27;]\n",
       "    predictiontime:  0\n",
       "    moduleflag:      8</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b8f6f70e-3f83-4798-bb9e-9bb3bf567120' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b8f6f70e-3f83-4798-bb9e-9bb3bf567120' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 1200</li><li><span class='xr-has-index'>x</span>: 1100</li><li><span class='xr-has-index'>time</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ea5b58b8-efeb-41fe-a28a-e4161df39054' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ea5b58b8-efeb-41fe-a28a-e4161df39054' class='xr-section-summary' >Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-04-09T12:00:00</div><input id='attrs-94817c87-fcc8-4c74-8a79-b47f5eaa6d39' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94817c87-fcc8-4c74-8a79-b47f5eaa6d39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cad14750-9cfb-47f6-97b0-bc643b84ee75' class='xr-var-data-in' type='checkbox'><label for='data-cad14750-9cfb-47f6-97b0-bc643b84ee75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-04-09T12:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.808e+06 ... -3.609e+06</div><input id='attrs-4ca82812-f7b0-40df-b3ae-855116026f2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4ca82812-f7b0-40df-b3ae-855116026f2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9adf24f1-8414-44b6-bbc8-f33431140222' class='xr-var-data-in' type='checkbox'><label for='data-9adf24f1-8414-44b6-bbc8-f33431140222' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-4808144.724266, -4807144.724266, -4806144.724266, ..., -3611144.724266,\n",
       "       -3610144.724266, -3609144.724266])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.43e+05 -5.42e+05 ... 5.56e+05</div><input id='attrs-24f69ec5-3365-46d9-8001-d90bbd954334' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24f69ec5-3365-46d9-8001-d90bbd954334' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-889b6202-cae7-4f1e-b989-d1d446e8ae08' class='xr-var-data-in' type='checkbox'><label for='data-889b6202-cae7-4f1e-b989-d1d446e8ae08' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-542962.166922, -541962.166922, -540962.166922, ...,  554037.833078,\n",
       "        555037.833078,  556037.833078])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x0</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.106e-09 1e+03 ... 1.099e+06</div><input id='attrs-f49970bb-faa2-491d-85c7-943f402e0a4d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f49970bb-faa2-491d-85c7-943f402e0a4d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73afed6b-7fee-4841-b237-3320885dfca0' class='xr-var-data-in' type='checkbox'><label for='data-73afed6b-7fee-4841-b237-3320885dfca0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1.10594556e-09, 1.00000000e+03, 2.00000000e+03, ...,\n",
       "       1.09700000e+06, 1.09800000e+06, 1.09900000e+06])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y0</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.199e+06 ... -2.794e-09</div><input id='attrs-c52753ba-eb40-4a5a-8fa5-2de5d855284a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c52753ba-eb40-4a5a-8fa5-2de5d855284a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac6d6a18-1173-46d5-adcd-8a6951069895' class='xr-var-data-in' type='checkbox'><label for='data-ac6d6a18-1173-46d5-adcd-8a6951069895' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-1.19900000e+06, -1.19800000e+06, -1.19700000e+06, ...,\n",
       "       -2.00000000e+03, -1.00000000e+03, -2.79396772e-09])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.557 3.569 3.581 ... 18.74 18.76</div><input id='attrs-9357fee5-f31e-4567-8c85-0a4b25fcb156' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9357fee5-f31e-4567-8c85-0a4b25fcb156' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d97a4503-9491-46f6-8bef-18fd8ed02dec' class='xr-var-data-in' type='checkbox'><label for='data-d97a4503-9491-46f6-8bef-18fd8ed02dec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 3.55713952,  3.56890614,  3.58067331, ..., 16.57314701,\n",
       "        16.58490698, 16.5966664 ],\n",
       "       [ 3.55581052,  3.56757953,  3.57934909, ..., 16.57450241,\n",
       "        16.58626476, 16.59802656],\n",
       "       [ 3.55448098,  3.56625238,  3.57802433, ..., 16.57585836,\n",
       "        16.5876231 , 16.59938728],\n",
       "       ...,\n",
       "       [ 1.44921109,  1.46472733,  1.48024484, ..., 18.72255664,\n",
       "        18.73805748, 18.75355704],\n",
       "       [ 1.44687757,  1.46239792,  1.47791953, ..., 18.72493559,\n",
       "        18.74044053, 18.75594418],\n",
       "       [ 1.44454279,  1.46006725,  1.47559297, ..., 18.72731583,\n",
       "        18.74282486, 18.75833261]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>45.7 45.7 45.7 ... 55.85 55.84</div><input id='attrs-42c6e96e-4bf2-4750-a7db-5e54b31c044a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-42c6e96e-4bf2-4750-a7db-5e54b31c044a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f00e5ac-54b8-4c33-b41a-77ce6b4719e8' class='xr-var-data-in' type='checkbox'><label for='data-1f00e5ac-54b8-4c33-b41a-77ce6b4719e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[45.70044344, 45.70137059, 45.70229606, ..., 45.69006221,\n",
       "        45.68911476, 45.68816563],\n",
       "       [45.7086614 , 45.7095888 , 45.71051451, ..., 45.69827743,\n",
       "        45.69732974, 45.69638036],\n",
       "       [45.71687983, 45.71780747, 45.71873343, ..., 45.70649312,\n",
       "        45.70554517, 45.70459555],\n",
       "       ...,\n",
       "       [55.84471987, 55.84602846, 55.84733471, ..., 55.83006925,\n",
       "        55.8287323 , 55.82739301],\n",
       "       [55.85343109, 55.8547401 , 55.85604676, ..., 55.83877582,\n",
       "        55.83743845, 55.83609873],\n",
       "       [55.86214267, 55.8634521 , 55.86475917, ..., 55.84748274,\n",
       "        55.84614495, 55.84480481]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-63016d9e-77fa-4f1b-a0fa-a84c911a51d9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-63016d9e-77fa-4f1b-a0fa-a84c911a51d9' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>WN</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fb83ef90-5011-482b-a10a-5152210decd4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fb83ef90-5011-482b-a10a-5152210decd4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8c46e0c-a784-43d7-a296-672811d51971' class='xr-var-data-in' type='checkbox'><label for='data-f8c46e0c-a784-43d7-a296-672811d51971' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>4095</dd><dt><span>standard_name :</span></dt><dd>equivalent_reflectivity_factor</dd><dt><span>long_name :</span></dt><dd>WN</dd><dt><span>unit :</span></dt><dd>dBZ</dd></dl></div><div class='xr-var-data'><pre>[1320000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a407c2d1-5af1-4022-9471-d7dec22bff5b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a407c2d1-5af1-4022-9471-d7dec22bff5b' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>radarid :</span></dt><dd>10000</dd><dt><span>formatversion :</span></dt><dd>3</dd><dt><span>radolanversion :</span></dt><dd>P300003H</dd><dt><span>radarlocations :</span></dt><dd>[&#x27;&#x27;]</dd><dt><span>predictiontime :</span></dt><dd>0</dd><dt><span>moduleflag :</span></dt><dd>8</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (y: 1200, x: 1100, time: 1)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2022-04-09T12:00:00\n",
       "  * y        (y) float64 -4.808e+06 -4.807e+06 ... -3.61e+06 -3.609e+06\n",
       "  * x        (x) float64 -5.43e+05 -5.42e+05 -5.41e+05 ... 5.55e+05 5.56e+05\n",
       "    x0       (x) float64 1.106e-09 1e+03 2e+03 ... 1.097e+06 1.098e+06 1.099e+06\n",
       "    y0       (y) float64 -1.199e+06 -1.198e+06 -1.197e+06 ... -1e+03 -2.794e-09\n",
       "    lon      (y, x) float64 3.557 3.569 3.581 3.592 ... 18.71 18.73 18.74 18.76\n",
       "    lat      (y, x) float64 45.7 45.7 45.7 45.7 45.7 ... 55.85 55.85 55.85 55.84\n",
       "Data variables:\n",
       "    WN       (y, x) float32 ...\n",
       "Attributes:\n",
       "    radarid:         10000\n",
       "    formatversion:   3\n",
       "    radolanversion:  P300003H\n",
       "    radarlocations:  ['']\n",
       "    predictiontime:  0\n",
       "    moduleflag:      8"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds1 = ds1.assign_coords({\"x0\": ([\"x\"], radolan_coords_de1200_sphere[0]),\n",
    "                         \"y0\": ([\"y\"], radolan_coords_de1200_sphere[1]),\n",
    "                         \"lon\": ([\"y\", \"x\"], radolan_grid_de1200_sphere[..., 0]),\n",
    "                         \"lat\": ([\"y\", \"x\"], radolan_grid_de1200_sphere[..., 1])})\n",
    "ds1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# center points of corner grid cells"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NW: 1.4445427919918514 55.86214266954008\n",
      "NO: 18.758332609073033 55.844804805996326\n",
      "SO: 16.596666395180193 45.6881656348777\n",
      "SW: 3.5571395161674375 45.700443437062944\n"
     ]
    }
   ],
   "source": [
    "print(\"NW:\", ds1.lon[-1, 0].values, ds1.lat[-1, 0].values)\n",
    "print(\"NO:\", ds1.lon[-1, -1].values, ds1.lat[-1, -1].values)\n",
    "print(\"SO:\", ds1.lon[0, -1].values, ds1.lat[0, -1].values)\n",
    "print(\"SW:\", ds1.lon[0, 0].values, ds1.lat[0, 0].values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visalization Sphere"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f015a43a4a0>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds1.WN.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f02c486d060>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds1.WN.plot(x=\"x0\", y=\"y0\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f028fecbfd0>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds1.WN.plot(x=\"lon\", y=\"lat\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (y: 1200, x: 1100, time: 1)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2022-04-09T12:00:00\n",
       "  * y        (y) float64 -4.808e+06 -4.807e+06 ... -3.61e+06 -3.609e+06\n",
       "  * x        (x) float64 -5.43e+05 -5.42e+05 -5.41e+05 ... 5.55e+05 5.56e+05\n",
       "    x0       (x) float64 -5.435e+05 -5.425e+05 ... 5.545e+05 5.555e+05\n",
       "    y0       (y) float64 -4.809e+06 -4.808e+06 ... -3.611e+06 -3.61e+06\n",
       "    lon      (y, x) float64 3.552 3.564 3.575 3.587 ... 18.7 18.72 18.73 18.75\n",
       "    lat      (y, x) float64 45.7 45.7 45.7 45.7 45.7 ... 55.85 55.84 55.84 55.84\n",
       "Data variables:\n",
       "    WN       (y, x) float32 ...\n",
       "Attributes:\n",
       "    radarid:         10000\n",
       "    formatversion:   3\n",
       "    radolanversion:  P300003H\n",
       "    radarlocations:  [&#x27;&#x27;]\n",
       "    predictiontime:  0\n",
       "    moduleflag:      8</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-ef4f1dfe-85f8-4938-86c5-27a1b80dcd21' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ef4f1dfe-85f8-4938-86c5-27a1b80dcd21' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 1200</li><li><span class='xr-has-index'>x</span>: 1100</li><li><span class='xr-has-index'>time</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f15adf89-fd7d-4e5f-9704-f43993c9fa0f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f15adf89-fd7d-4e5f-9704-f43993c9fa0f' class='xr-section-summary' >Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-04-09T12:00:00</div><input id='attrs-7fc27b3c-b17e-4ca2-9bb4-1f27a55d6916' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7fc27b3c-b17e-4ca2-9bb4-1f27a55d6916' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5a07813-44c1-4b26-be2f-b4b7eb60ba35' class='xr-var-data-in' type='checkbox'><label for='data-f5a07813-44c1-4b26-be2f-b4b7eb60ba35' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-04-09T12:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.808e+06 ... -3.609e+06</div><input id='attrs-dd08968d-76f6-41b9-a505-03b9fd14bae4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd08968d-76f6-41b9-a505-03b9fd14bae4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31cd9688-05d6-4cb5-89f1-83e07b7f6d41' class='xr-var-data-in' type='checkbox'><label for='data-31cd9688-05d6-4cb5-89f1-83e07b7f6d41' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-4808144.724266, -4807144.724266, -4806144.724266, ..., -3611144.724266,\n",
       "       -3610144.724266, -3609144.724266])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.43e+05 -5.42e+05 ... 5.56e+05</div><input id='attrs-3bb5519e-8a51-4061-a5ba-83a499b19aa3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3bb5519e-8a51-4061-a5ba-83a499b19aa3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e522867f-c485-458e-9293-ee685d981183' class='xr-var-data-in' type='checkbox'><label for='data-e522867f-c485-458e-9293-ee685d981183' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-542962.166922, -541962.166922, -540962.166922, ...,  554037.833078,\n",
       "        555037.833078,  556037.833078])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x0</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.435e+05 -5.425e+05 ... 5.555e+05</div><input id='attrs-f26a6e3a-60a7-442b-a7a2-b56f92e68ce3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f26a6e3a-60a7-442b-a7a2-b56f92e68ce3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a7cfa34d-652b-4660-8b59-7a89e5fc3407' class='xr-var-data-in' type='checkbox'><label for='data-a7cfa34d-652b-4660-8b59-7a89e5fc3407' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-543462.16692186, -542462.16692186, -541462.16692186, ...,\n",
       "        553537.83307814,  554537.83307814,  555537.83307814])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y0</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.809e+06 -4.808e+06 ... -3.61e+06</div><input id='attrs-b3f936e9-3936-4ea8-948b-f6346163eb6e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b3f936e9-3936-4ea8-948b-f6346163eb6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e785227-a23b-4bb6-b161-17a85ff6f561' class='xr-var-data-in' type='checkbox'><label for='data-8e785227-a23b-4bb6-b161-17a85ff6f561' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-4808644.72426557, -4807644.72426557, -4806644.72426557, ...,\n",
       "       -3611644.72426557, -3610644.72426557, -3609644.72426557])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.552 3.564 3.575 ... 18.73 18.75</div><input id='attrs-de3361ee-600d-4fdf-8144-32c765947bac' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-de3361ee-600d-4fdf-8144-32c765947bac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9bda213-ed46-4e19-9b42-a1f15df9e3d3' class='xr-var-data-in' type='checkbox'><label for='data-e9bda213-ed46-4e19-9b42-a1f15df9e3d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 3.5519213 ,  3.56368646,  3.57545216, ..., 16.56658991,\n",
       "        16.57834898, 16.59010748],\n",
       "       [ 3.55059138,  3.56235893,  3.57412702, ..., 16.56794385,\n",
       "        16.57970529, 16.59146617],\n",
       "       [ 3.54926092,  3.56103085,  3.57280133, ..., 16.56929833,\n",
       "        16.58106216, 16.59282543],\n",
       "       ...,\n",
       "       [ 1.44262076,  1.45813431,  1.47364913, ..., 18.71361777,\n",
       "        18.72911721, 18.74461536],\n",
       "       [ 1.44028582,  1.45580348,  1.47132241, ..., 18.71599403,\n",
       "        18.73149756, 18.74699981],\n",
       "       [ 1.43794961,  1.45347139,  1.46899442, ..., 18.71837157,\n",
       "        18.7338792 , 18.74938554]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>45.7 45.7 45.7 ... 55.84 55.84</div><input id='attrs-8c02e084-5310-44d1-b594-b8d2d61d3f0d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8c02e084-5310-44d1-b594-b8d2d61d3f0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59439f34-bf76-4520-8669-a66fc70f6501' class='xr-var-data-in' type='checkbox'><label for='data-59439f34-bf76-4520-8669-a66fc70f6501' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[45.69587048, 45.69679835, 45.69772454, ..., 45.6864278 ,\n",
       "        45.68548131, 45.68453315],\n",
       "       [45.7040881 , 45.70501621, 45.70594264, ..., 45.69464292,\n",
       "        45.69369619, 45.69274778],\n",
       "       [45.71230617, 45.71323453, 45.7141612 , ..., 45.7028585 ,\n",
       "        45.70191152, 45.70096286],\n",
       "       ...,\n",
       "       [55.83970931, 55.84101888, 55.84232609, ..., 55.82638358,\n",
       "        55.82504802, 55.82371011],\n",
       "       [55.84842015, 55.84973013, 55.85103776, ..., 55.83509019,\n",
       "        55.8337542 , 55.83241587],\n",
       "       [55.85713135, 55.85844174, 55.85974978, ..., 55.84379715,\n",
       "        55.84246074, 55.84112198]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-96b3d12e-82ed-489f-b407-3bf837e4aa3a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-96b3d12e-82ed-489f-b407-3bf837e4aa3a' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>WN</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-12f5fc3c-fee1-4c46-989f-cbf87fa06074' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-12f5fc3c-fee1-4c46-989f-cbf87fa06074' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-352fbfe3-74c9-42e5-949f-db2b9daa8377' class='xr-var-data-in' type='checkbox'><label for='data-352fbfe3-74c9-42e5-949f-db2b9daa8377' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>4095</dd><dt><span>standard_name :</span></dt><dd>equivalent_reflectivity_factor</dd><dt><span>long_name :</span></dt><dd>WN</dd><dt><span>unit :</span></dt><dd>dBZ</dd></dl></div><div class='xr-var-data'><pre>[1320000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-741793b3-5eed-4cb9-8d6f-896450b642ee' class='xr-section-summary-in' type='checkbox'  checked><label for='section-741793b3-5eed-4cb9-8d6f-896450b642ee' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>radarid :</span></dt><dd>10000</dd><dt><span>formatversion :</span></dt><dd>3</dd><dt><span>radolanversion :</span></dt><dd>P300003H</dd><dt><span>radarlocations :</span></dt><dd>[&#x27;&#x27;]</dd><dt><span>predictiontime :</span></dt><dd>0</dd><dt><span>moduleflag :</span></dt><dd>8</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (y: 1200, x: 1100, time: 1)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2022-04-09T12:00:00\n",
       "  * y        (y) float64 -4.808e+06 -4.807e+06 ... -3.61e+06 -3.609e+06\n",
       "  * x        (x) float64 -5.43e+05 -5.42e+05 -5.41e+05 ... 5.55e+05 5.56e+05\n",
       "    x0       (x) float64 -5.435e+05 -5.425e+05 ... 5.545e+05 5.555e+05\n",
       "    y0       (y) float64 -4.809e+06 -4.808e+06 ... -3.611e+06 -3.61e+06\n",
       "    lon      (y, x) float64 3.552 3.564 3.575 3.587 ... 18.7 18.72 18.73 18.75\n",
       "    lat      (y, x) float64 45.7 45.7 45.7 45.7 45.7 ... 55.85 55.84 55.84 55.84\n",
       "Data variables:\n",
       "    WN       (y, x) float32 ...\n",
       "Attributes:\n",
       "    radarid:         10000\n",
       "    formatversion:   3\n",
       "    radolanversion:  P300003H\n",
       "    radarlocations:  ['']\n",
       "    predictiontime:  0\n",
       "    moduleflag:      8"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds2 = ds1.assign_coords({\"x0\": ([\"x\"], radolan_coords[0] * 1000),\n",
    "                         \"y0\": ([\"y\"], radolan_coords[1] * 1000),\n",
    "                         \"lon\": ([\"y\", \"x\"], radolan_grid[..., 0]),\n",
    "                         \"lat\": ([\"y\", \"x\"], radolan_grid[..., 1])})\n",
    "ds2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# cartopy map projections"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "map_proj_wgs84_new = ccrs.Stereographic(true_scale_latitude=60., central_latitude=90., central_longitude=10.,\n",
    "                                        false_easting=543196.83521776402, false_northing=3622588.8619310018)\n",
    "\n",
    "map_proj_wgs84_old = ccrs.Stereographic(true_scale_latitude=60., central_latitude=90., central_longitude=10.,\n",
    "                                        false_easting=0., false_northing=0.)\n",
    "\n",
    "sphere = ccrs.Globe(ellipse=\"sphere\", semimajor_axis=\"6370040\", semiminor_axis=\"6370040\")\n",
    "map_proj_sphere_old = ccrs.Stereographic(true_scale_latitude=60., central_latitude=90., central_longitude=10., \n",
    "                                     globe=sphere,\n",
    "                                     false_easting=0, false_northing=0)\n",
    "map_proj_sphere_new = ccrs.Stereographic(true_scale_latitude=60., central_latitude=90., central_longitude=10., \n",
    "                                     globe=sphere,\n",
    "                                     false_easting=542962.16692185658, false_northing=3609144.7242655745)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# plot centroids on top of pcolormesh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# slice lower left corner\n",
    "sl0 = ds0.WN.isel(x=slice(0, 8), y=slice(0, 8))\n",
    "sl1 = ds1.WN.isel(x=slice(0, 8), y=slice(0, 8))\n",
    "sl2 = ds2.WN.isel(x=slice(0, 8), y=slice(0, 8))\n",
    "\n",
    "# fill data\n",
    "sl0.values.flat[:-8] = np.arange(56)\n",
    "sl1.values.flat[8:] = np.arange(56)\n",
    "sl2.values.flat[:-8] = np.arange(56)\n",
    "\n",
    "# convert original km-based projection to meter\n",
    "sl0a = sl0.pint.quantify()\n",
    "sl0a = sl0a.pint.to(x=\"m\", y=\"m\")\n",
    "sl1a = sl0.pint.quantify()\n",
    "sl1a = sl0a.pint.to(x=\"m\", y=\"m\")\n",
    "sl2a = sl2.pint.quantify()\n",
    "sl2a = sl2a.pint.to(x=\"m\", y=\"m\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;WN&#x27; (y: 8, x: 8)&gt;\n",
       "array([[ 0.,  1.,  2.,  3.,  4.,  5.,  6.,  7.],\n",
       "       [ 8.,  9., 10., 11., 12., 13., 14., 15.],\n",
       "       [16., 17., 18., 19., 20., 21., 22., 23.],\n",
       "       [24., 25., 26., 27., 28., 29., 30., 31.],\n",
       "       [32., 33., 34., 35., 36., 37., 38., 39.],\n",
       "       [40., 41., 42., 43., 44., 45., 46., 47.],\n",
       "       [48., 49., 50., 51., 52., 53., 54., 55.],\n",
       "       [nan, nan, nan, nan, nan, nan, nan, nan]], dtype=float32)\n",
       "Coordinates:\n",
       "  * y        (y) float64 -4.822e+06 -4.821e+06 ... -4.816e+06 -4.815e+06\n",
       "  * x        (x) float64 -5.432e+05 -5.422e+05 ... -5.372e+05 -5.362e+05\n",
       "    x0       (x) float64 6.123e-08 1e+03 2e+03 3e+03 4e+03 5e+03 6e+03 7e+03\n",
       "    y0       (y) float64 -1.199e+06 -1.198e+06 ... -1.193e+06 -1.192e+06\n",
       "    lon      (y, x) float64 3.572 3.584 3.596 3.607 ... 3.61 3.622 3.633 3.645\n",
       "    lat      (y, x) float64 45.7 45.7 45.7 45.7 45.7 ... 45.76 45.76 45.76 45.77\n",
       "Attributes:\n",
       "    valid_min:      0\n",
       "    valid_max:      4095\n",
       "    standard_name:  equivalent_reflectivity_factor\n",
       "    long_name:      WN\n",
       "    unit:           dBZ</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'WN'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 8</li><li><span class='xr-has-index'>x</span>: 8</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-364a77ad-9f5b-4687-8b70-ca19916ad4f9' class='xr-array-in' type='checkbox' checked><label for='section-364a77ad-9f5b-4687-8b70-ca19916ad4f9' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 ... nan nan nan nan nan nan nan nan</span></div><div class='xr-array-data'><pre>array([[ 0.,  1.,  2.,  3.,  4.,  5.,  6.,  7.],\n",
       "       [ 8.,  9., 10., 11., 12., 13., 14., 15.],\n",
       "       [16., 17., 18., 19., 20., 21., 22., 23.],\n",
       "       [24., 25., 26., 27., 28., 29., 30., 31.],\n",
       "       [32., 33., 34., 35., 36., 37., 38., 39.],\n",
       "       [40., 41., 42., 43., 44., 45., 46., 47.],\n",
       "       [48., 49., 50., 51., 52., 53., 54., 55.],\n",
       "       [nan, nan, nan, nan, nan, nan, nan, nan]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-cf6b9336-99dc-4f27-b487-2fe88f043822' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cf6b9336-99dc-4f27-b487-2fe88f043822' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.822e+06 ... -4.815e+06</div><input id='attrs-b3c93236-9c79-4a2c-8eef-c35bdf81170d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b3c93236-9c79-4a2c-8eef-c35bdf81170d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc64b758-b2bb-42c5-9279-782c90f75d30' class='xr-var-data-in' type='checkbox'><label for='data-bc64b758-b2bb-42c5-9279-782c90f75d30' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-4821588.861931, -4820588.861931, -4819588.861931, -4818588.861931,\n",
       "       -4817588.861931, -4816588.861931, -4815588.861931, -4814588.861931])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.432e+05 ... -5.362e+05</div><input id='attrs-481a286f-cd13-4bbf-b85b-ce3a101e1b3b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-481a286f-cd13-4bbf-b85b-ce3a101e1b3b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21991eb5-3f9f-4890-8e36-c15687e4c145' class='xr-var-data-in' type='checkbox'><label for='data-21991eb5-3f9f-4890-8e36-c15687e4c145' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-543196.835218, -542196.835218, -541196.835218, -540196.835218,\n",
       "       -539196.835218, -538196.835218, -537196.835218, -536196.835218])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x0</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.123e-08 1e+03 ... 6e+03 7e+03</div><input id='attrs-00278118-dcfb-41fc-809a-a79f40b38753' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-00278118-dcfb-41fc-809a-a79f40b38753' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ffbbe5d-63d6-4b32-b6d6-6406658043e6' class='xr-var-data-in' type='checkbox'><label for='data-6ffbbe5d-63d6-4b32-b6d6-6406658043e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6.12344593e-08, 1.00000000e+03, 2.00000000e+03, 3.00000000e+03,\n",
       "       4.00000000e+03, 5.00000000e+03, 6.00000000e+03, 7.00000000e+03])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y0</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.199e+06 ... -1.192e+06</div><input id='attrs-0ce2acc0-57aa-4d84-b58f-bdea69c8c836' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0ce2acc0-57aa-4d84-b58f-bdea69c8c836' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7826a9c8-680c-4e37-80e4-1b152fe3216d' class='xr-var-data-in' type='checkbox'><label for='data-7826a9c8-680c-4e37-80e4-1b152fe3216d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-1198999.99999959, -1197999.99999959, -1196999.99999959,\n",
       "       -1195999.99999959, -1194999.99999959, -1193999.99999959,\n",
       "       -1192999.99999959, -1191999.99999959])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.572 3.584 3.596 ... 3.633 3.645</div><input id='attrs-bb768b36-9419-4853-b54d-256354f8b494' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bb768b36-9419-4853-b54d-256354f8b494' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-642e6598-c2dd-4d20-afab-35463f20c814' class='xr-var-data-in' type='checkbox'><label for='data-642e6598-c2dd-4d20-afab-35463f20c814' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[3.57220018, 3.58393469, 3.59566974, 3.60740533, 3.61914147,\n",
       "        3.63087813, 3.64261534, 3.65435308],\n",
       "       [3.57087793, 3.58261482, 3.59435225, 3.60609021, 3.61782872,\n",
       "        3.62956776, 3.64130734, 3.65304746],\n",
       "       [3.56955515, 3.58129441, 3.59303421, 3.60477455, 3.61651543,\n",
       "        3.62825685, 3.63999881, 3.6517413 ],\n",
       "       [3.56823182, 3.57997346, 3.59171564, 3.60345835, 3.61520161,\n",
       "        3.62694541, 3.63868974, 3.65043461],\n",
       "       [3.56690796, 3.57865197, 3.59039652, 3.60214161, 3.61388725,\n",
       "        3.62563342, 3.63738013, 3.64912738],\n",
       "       [3.56558354, 3.57732993, 3.58907686, 3.60082433, 3.61257235,\n",
       "        3.6243209 , 3.63606999, 3.64781962],\n",
       "       [3.56425859, 3.57600736, 3.58775666, 3.59950652, 3.61125691,\n",
       "        3.62300784, 3.63475931, 3.64651131],\n",
       "       [3.56293309, 3.57468424, 3.58643593, 3.59818816, 3.60994093,\n",
       "        3.62169424, 3.63344809, 3.64520248]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>45.7 45.7 45.7 ... 45.76 45.77</div><input id='attrs-0f91e898-5582-4285-b63d-2771abb17576' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0f91e898-5582-4285-b63d-2771abb17576' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33f35254-8fcd-4380-b34f-f0e5fe720bee' class='xr-var-data-in' type='checkbox'><label for='data-33f35254-8fcd-4380-b34f-f0e5fe720bee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[45.70099971, 45.70192517, 45.70284896, 45.70377107, 45.7046915 ,\n",
       "        45.70561025, 45.70652732, 45.70744271],\n",
       "       [45.7092221 , 45.7101478 , 45.71107183, 45.71199418, 45.71291485,\n",
       "        45.71383384, 45.71475116, 45.71566679],\n",
       "       [45.71744493, 45.71837088, 45.71929515, 45.72021774, 45.72113865,\n",
       "        45.72205789, 45.72297544, 45.72389131],\n",
       "       [45.72566821, 45.7265944 , 45.72751892, 45.72844175, 45.7293629 ,\n",
       "        45.73028237, 45.73120017, 45.73211628],\n",
       "       [45.73389194, 45.73481837, 45.73574313, 45.7366662 , 45.73758759,\n",
       "        45.73850731, 45.73942534, 45.74034169],\n",
       "       [45.74211611, 45.74304279, 45.74396778, 45.7448911 , 45.74581273,\n",
       "        45.74673269, 45.74765096, 45.74856755],\n",
       "       [45.75034073, 45.75126765, 45.75219288, 45.75311644, 45.75403832,\n",
       "        45.75495851, 45.75587703, 45.75679386],\n",
       "       [45.75856579, 45.75949295, 45.76041843, 45.76134223, 45.76226435,\n",
       "        45.76318478, 45.76410354, 45.76502061]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a44c49a0-730a-4493-b577-2f6bed412006' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a44c49a0-730a-4493-b577-2f6bed412006' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>4095</dd><dt><span>standard_name :</span></dt><dd>equivalent_reflectivity_factor</dd><dt><span>long_name :</span></dt><dd>WN</dd><dt><span>unit :</span></dt><dd>dBZ</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'WN' (y: 8, x: 8)>\n",
       "array([[ 0.,  1.,  2.,  3.,  4.,  5.,  6.,  7.],\n",
       "       [ 8.,  9., 10., 11., 12., 13., 14., 15.],\n",
       "       [16., 17., 18., 19., 20., 21., 22., 23.],\n",
       "       [24., 25., 26., 27., 28., 29., 30., 31.],\n",
       "       [32., 33., 34., 35., 36., 37., 38., 39.],\n",
       "       [40., 41., 42., 43., 44., 45., 46., 47.],\n",
       "       [48., 49., 50., 51., 52., 53., 54., 55.],\n",
       "       [nan, nan, nan, nan, nan, nan, nan, nan]], dtype=float32)\n",
       "Coordinates:\n",
       "  * y        (y) float64 -4.822e+06 -4.821e+06 ... -4.816e+06 -4.815e+06\n",
       "  * x        (x) float64 -5.432e+05 -5.422e+05 ... -5.372e+05 -5.362e+05\n",
       "    x0       (x) float64 6.123e-08 1e+03 2e+03 3e+03 4e+03 5e+03 6e+03 7e+03\n",
       "    y0       (y) float64 -1.199e+06 -1.198e+06 ... -1.193e+06 -1.192e+06\n",
       "    lon      (y, x) float64 3.572 3.584 3.596 3.607 ... 3.61 3.622 3.633 3.645\n",
       "    lat      (y, x) float64 45.7 45.7 45.7 45.7 45.7 ... 45.76 45.76 45.76 45.77\n",
       "Attributes:\n",
       "    valid_min:      0\n",
       "    valid_max:      4095\n",
       "    standard_name:  equivalent_reflectivity_factor\n",
       "    long_name:      WN\n",
       "    unit:           dBZ"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sl0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
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       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;WN&#x27; (y: 8, x: 8)&gt;\n",
       "array([[nan, nan, nan, nan, nan, nan, nan, nan],\n",
       "       [ 0.,  1.,  2.,  3.,  4.,  5.,  6.,  7.],\n",
       "       [ 8.,  9., 10., 11., 12., 13., 14., 15.],\n",
       "       [16., 17., 18., 19., 20., 21., 22., 23.],\n",
       "       [24., 25., 26., 27., 28., 29., 30., 31.],\n",
       "       [32., 33., 34., 35., 36., 37., 38., 39.],\n",
       "       [40., 41., 42., 43., 44., 45., 46., 47.],\n",
       "       [48., 49., 50., 51., 52., 53., 54., 55.]], dtype=float32)\n",
       "Coordinates:\n",
       "  * y        (y) float64 -4.808e+06 -4.807e+06 ... -4.802e+06 -4.801e+06\n",
       "  * x        (x) float64 -5.43e+05 -5.42e+05 -5.41e+05 ... -5.37e+05 -5.36e+05\n",
       "    x0       (x) float64 1.106e-09 1e+03 2e+03 3e+03 4e+03 5e+03 6e+03 7e+03\n",
       "    y0       (y) float64 -1.199e+06 -1.198e+06 ... -1.193e+06 -1.192e+06\n",
       "    lon      (y, x) float64 3.557 3.569 3.581 3.592 ... 3.595 3.607 3.619 3.63\n",
       "    lat      (y, x) float64 45.7 45.7 45.7 45.7 45.7 ... 45.76 45.76 45.76 45.76\n",
       "Attributes:\n",
       "    valid_min:      0\n",
       "    valid_max:      4095\n",
       "    standard_name:  equivalent_reflectivity_factor\n",
       "    long_name:      WN\n",
       "    unit:           dBZ</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'WN'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 8</li><li><span class='xr-has-index'>x</span>: 8</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-f6660d2a-5797-4d28-97e3-32132dc46c87' class='xr-array-in' type='checkbox' checked><label for='section-f6660d2a-5797-4d28-97e3-32132dc46c87' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>nan nan nan nan nan nan nan nan ... 49.0 50.0 51.0 52.0 53.0 54.0 55.0</span></div><div class='xr-array-data'><pre>array([[nan, nan, nan, nan, nan, nan, nan, nan],\n",
       "       [ 0.,  1.,  2.,  3.,  4.,  5.,  6.,  7.],\n",
       "       [ 8.,  9., 10., 11., 12., 13., 14., 15.],\n",
       "       [16., 17., 18., 19., 20., 21., 22., 23.],\n",
       "       [24., 25., 26., 27., 28., 29., 30., 31.],\n",
       "       [32., 33., 34., 35., 36., 37., 38., 39.],\n",
       "       [40., 41., 42., 43., 44., 45., 46., 47.],\n",
       "       [48., 49., 50., 51., 52., 53., 54., 55.]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-4beb78aa-0c7c-490c-bd62-52c8ecb9a314' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4beb78aa-0c7c-490c-bd62-52c8ecb9a314' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.808e+06 ... -4.801e+06</div><input id='attrs-95daaf8c-be6f-47ae-9b43-515669a517ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95daaf8c-be6f-47ae-9b43-515669a517ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84d3e34b-2afd-49d2-858e-4959b64fb7d3' class='xr-var-data-in' type='checkbox'><label for='data-84d3e34b-2afd-49d2-858e-4959b64fb7d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-4808144.724266, -4807144.724266, -4806144.724266, -4805144.724266,\n",
       "       -4804144.724266, -4803144.724266, -4802144.724266, -4801144.724266])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.43e+05 -5.42e+05 ... -5.36e+05</div><input id='attrs-29d82194-3010-4be2-95f2-f96b5f262294' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29d82194-3010-4be2-95f2-f96b5f262294' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0062658f-1e75-43d3-bd0b-f265a75e5362' class='xr-var-data-in' type='checkbox'><label for='data-0062658f-1e75-43d3-bd0b-f265a75e5362' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-542962.166922, -541962.166922, -540962.166922, -539962.166922,\n",
       "       -538962.166922, -537962.166922, -536962.166922, -535962.166922])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x0</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.106e-09 1e+03 ... 6e+03 7e+03</div><input id='attrs-3233e6f2-10a4-4b57-a2f7-0d7777c594f7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3233e6f2-10a4-4b57-a2f7-0d7777c594f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e803088d-caa1-493f-b90b-809d109b4615' class='xr-var-data-in' type='checkbox'><label for='data-e803088d-caa1-493f-b90b-809d109b4615' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1.10594556e-09, 1.00000000e+03, 2.00000000e+03, 3.00000000e+03,\n",
       "       4.00000000e+03, 5.00000000e+03, 6.00000000e+03, 7.00000000e+03])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y0</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.199e+06 ... -1.192e+06</div><input id='attrs-1a48fcd4-93d1-46f7-ba13-e7f8519c8d05' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a48fcd4-93d1-46f7-ba13-e7f8519c8d05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d3a81cd-77ff-42e1-9c17-23bff415c0bc' class='xr-var-data-in' type='checkbox'><label for='data-6d3a81cd-77ff-42e1-9c17-23bff415c0bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-1199000., -1198000., -1197000., -1196000., -1195000., -1194000.,\n",
       "       -1193000., -1192000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.557 3.569 3.581 ... 3.619 3.63</div><input id='attrs-5a742d3b-f27f-4264-83ef-ae7e88589a85' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5a742d3b-f27f-4264-83ef-ae7e88589a85' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b28086a-1678-46d2-9c91-69d0dcf9940b' class='xr-var-data-in' type='checkbox'><label for='data-9b28086a-1678-46d2-9c91-69d0dcf9940b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[3.55713952, 3.56890614, 3.58067331, 3.59244103, 3.60420929,\n",
       "        3.61597809, 3.62774743, 3.63951731],\n",
       "       [3.55581052, 3.56757953, 3.57934909, 3.5911192 , 3.60288984,\n",
       "        3.61466103, 3.62643276, 3.63820503],\n",
       "       [3.55448098, 3.56625238, 3.57802433, 3.58979682, 3.60156985,\n",
       "        3.61334343, 3.62511755, 3.6368922 ],\n",
       "       [3.55315089, 3.56492468, 3.57669902, 3.5884739 , 3.60024932,\n",
       "        3.61202528, 3.62380179, 3.63557884],\n",
       "       [3.55182026, 3.56359644, 3.57537316, 3.58715043, 3.59892824,\n",
       "        3.6107066 , 3.6224855 , 3.63426494],\n",
       "       [3.55048908, 3.56226765, 3.57404676, 3.58582642, 3.59760662,\n",
       "        3.60938737, 3.62116866, 3.63295049],\n",
       "       [3.54915735, 3.56093831, 3.57271982, 3.58450187, 3.59628446,\n",
       "        3.6080676 , 3.61985129, 3.63163551],\n",
       "       [3.54782508, 3.55960843, 3.57139232, 3.58317677, 3.59496176,\n",
       "        3.60674729, 3.61853337, 3.63031998]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>45.7 45.7 45.7 ... 45.76 45.76</div><input id='attrs-7c4e0d2a-2b3d-479f-83d0-005ec3e89d3e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7c4e0d2a-2b3d-479f-83d0-005ec3e89d3e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3dc2bbdd-12f4-4bed-87da-bdfff682c836' class='xr-var-data-in' type='checkbox'><label for='data-3dc2bbdd-12f4-4bed-87da-bdfff682c836' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[45.70044344, 45.70137059, 45.70229606, 45.70321985, 45.70414195,\n",
       "        45.70506238, 45.70598112, 45.70689818],\n",
       "       [45.7086614 , 45.7095888 , 45.71051451, 45.71143854, 45.71236089,\n",
       "        45.71328156, 45.71420054, 45.71511784],\n",
       "       [45.71687983, 45.71780747, 45.71873343, 45.7196577 , 45.72058029,\n",
       "        45.7215012 , 45.72242043, 45.72333797],\n",
       "       [45.72509871, 45.72602659, 45.7269528 , 45.72787732, 45.72880015,\n",
       "        45.7297213 , 45.73064077, 45.73155856],\n",
       "       [45.73331805, 45.73424618, 45.73517263, 45.73609739, 45.73702047,\n",
       "        45.73794186, 45.73886158, 45.7397796 ],\n",
       "       [45.74153785, 45.74246622, 45.74339291, 45.74431792, 45.74524124,\n",
       "        45.74616288, 45.74708284, 45.74800111],\n",
       "       [45.7497581 , 45.75068672, 45.75161366, 45.75253891, 45.75346248,\n",
       "        45.75438436, 45.75530456, 45.75622307],\n",
       "       [45.75797882, 45.75890768, 45.75983486, 45.76076036, 45.76168417,\n",
       "        45.76260629, 45.76352674, 45.76444549]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-450b811b-4233-4f6e-9305-4d3b2d1c2990' class='xr-section-summary-in' type='checkbox'  checked><label for='section-450b811b-4233-4f6e-9305-4d3b2d1c2990' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>4095</dd><dt><span>standard_name :</span></dt><dd>equivalent_reflectivity_factor</dd><dt><span>long_name :</span></dt><dd>WN</dd><dt><span>unit :</span></dt><dd>dBZ</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'WN' (y: 8, x: 8)>\n",
       "array([[nan, nan, nan, nan, nan, nan, nan, nan],\n",
       "       [ 0.,  1.,  2.,  3.,  4.,  5.,  6.,  7.],\n",
       "       [ 8.,  9., 10., 11., 12., 13., 14., 15.],\n",
       "       [16., 17., 18., 19., 20., 21., 22., 23.],\n",
       "       [24., 25., 26., 27., 28., 29., 30., 31.],\n",
       "       [32., 33., 34., 35., 36., 37., 38., 39.],\n",
       "       [40., 41., 42., 43., 44., 45., 46., 47.],\n",
       "       [48., 49., 50., 51., 52., 53., 54., 55.]], dtype=float32)\n",
       "Coordinates:\n",
       "  * y        (y) float64 -4.808e+06 -4.807e+06 ... -4.802e+06 -4.801e+06\n",
       "  * x        (x) float64 -5.43e+05 -5.42e+05 -5.41e+05 ... -5.37e+05 -5.36e+05\n",
       "    x0       (x) float64 1.106e-09 1e+03 2e+03 3e+03 4e+03 5e+03 6e+03 7e+03\n",
       "    y0       (y) float64 -1.199e+06 -1.198e+06 ... -1.193e+06 -1.192e+06\n",
       "    lon      (y, x) float64 3.557 3.569 3.581 3.592 ... 3.595 3.607 3.619 3.63\n",
       "    lat      (y, x) float64 45.7 45.7 45.7 45.7 45.7 ... 45.76 45.76 45.76 45.76\n",
       "Attributes:\n",
       "    valid_min:      0\n",
       "    valid_max:      4095\n",
       "    standard_name:  equivalent_reflectivity_factor\n",
       "    long_name:      WN\n",
       "    unit:           dBZ"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sl1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting lonlat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f02b76b5fc0>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create figure\n",
    "fig = pl.figure(figsize=(14, 8))\n",
    "\n",
    "# create projection subplot\n",
    "ax = fig.add_subplot(111, projection=ccrs.PlateCarree())\n",
    "\n",
    "# plot pcolormesh for new wgs84 grid\n",
    "sl0.plot(x=\"lon\", y=\"lat\", ax=ax, infer_intervals=False, transform=ccrs.PlateCarree(), zorder=-2)\n",
    "# plot centroid scatter for new wgs84\n",
    "ax.scatter(sl0.lon, sl0.lat, c=\"r\", transform=ccrs.PlateCarree(), label=\"wgs84 - new\")\n",
    "\n",
    "# plot pcolormesh for new sphere grid\n",
    "sl1.plot(x=\"lon\", y=\"lat\", ax=ax, infer_intervals=False, transform=ccrs.PlateCarree(), zorder=-3, add_colorbar=False)\n",
    "# plot centroid scatter for new sphere \n",
    "ax.scatter(sl1.lon, sl1.lat, c=\"b\", transform=ccrs.PlateCarree(), label=\"sphere - new\")\n",
    "\n",
    "# plot pcolormesh for old sphere grid\n",
    "sl2a.plot(x=\"lon\", y=\"lat\", ax=ax, infer_intervals=True, transform=ccrs.PlateCarree(), zorder=-4, add_colorbar=False)\n",
    "# plot centroid scatter for old sphere\n",
    "ax.scatter(sl2.lon, sl2.lat, c=\"c\", transform=ccrs.PlateCarree(), label=\"sphere - old\")\n",
    "\n",
    "ax.gridlines(draw_labels=True)\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting polar stereographic  1 (1D coords)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f02b764bdc0>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create figure\n",
    "fig = pl.figure(figsize=(14, 8))\n",
    "\n",
    "# create projection subplot\n",
    "ax = fig.add_subplot(111, projection=ccrs.PlateCarree())\n",
    "\n",
    "sl0.plot(x=\"x\", y=\"y\", ax=ax, infer_intervals=False, transform=map_proj_wgs84_old, zorder=-2)\n",
    "# plot centroid scatter for new wgs84\n",
    "ax.scatter(sl0.x, sl0.y, c=\"r\", transform=map_proj_wgs84_old, label=\"wgs84 - new\")\n",
    "\n",
    "# plot pcolormesh for new sphere grid\n",
    "sl1.plot(x=\"x\", y=\"y\", ax=ax, infer_intervals=False, transform=map_proj_sphere_old, zorder=-3, add_colorbar=False)\n",
    "# plot centroid scatter for new sphere \n",
    "ax.scatter(sl1.x, sl1.y, c=\"b\", transform=map_proj_sphere_old, label=\"sphere - new\")\n",
    "\n",
    "ax.gridlines(draw_labels=True)\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# plotting polar stereographic 2 (2D coords)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f033c20f790>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create figure\n",
    "fig = pl.figure(figsize=(14, 8))\n",
    "\n",
    "# create projection subplot\n",
    "ax = fig.add_subplot(111, projection=ccrs.PlateCarree())\n",
    "\n",
    "# plot pcolormesh for new wgs84 grid\n",
    "sl0.plot(x=\"x0\", y=\"y0\", ax=ax, infer_intervals=False, transform=map_proj_wgs84_new, zorder=-2)\n",
    "# plot centroid scatter for new wgs84\n",
    "ax.scatter(sl0.x0, sl0.y0, c=\"r\", transform=map_proj_wgs84_new, label=\"wgs84 - new\")\n",
    "\n",
    "# plot pcolormesh for new sphere grid\n",
    "sl1.plot(x=\"x0\", y=\"y0\", ax=ax, infer_intervals=False, transform=map_proj_sphere_new, zorder=-3, add_colorbar=False)\n",
    "# plot centroid scatter for new sphere \n",
    "ax.scatter(sl1.x0, sl1.y0, c=\"b\", transform=map_proj_sphere_new, label=\"sphere - new\")\n",
    "\n",
    "# plot pcolormesh for old sphere grid\n",
    "sl2.plot(x=\"x0\", y=\"y0\", ax=ax, infer_intervals=True, transform=map_proj_sphere_old, zorder=-4, add_colorbar=False)\n",
    "# plot centroid scatter for old sphere\n",
    "ax.scatter(sl2.x0, sl2.y0, c=\"c\", transform=map_proj_sphere_old, label=\"sphere - old\")\n",
    "\n",
    "ax.gridlines(draw_labels=True)\n",
    "ax.legend()"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "4dfe7fd749d0582002c1fcd24a760f55751becedafed20ea0ade6306c4a5829d"
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}