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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Satellite images are returned by Python AWIPS as grids, and can be rendered with Cartopy pcolormesh the same as gridded forecast models in other python-awips examples. "
]
},
{
"cell_type": "code",
"execution_count": 80,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"from awips.dataaccess import DataAccessLayer\n",
"import cartopy.crs as ccrs\n",
"import cartopy.feature as cfeat\n",
"import matplotlib.pyplot as plt\n",
"from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER\n",
"import numpy as np\n",
"import datetime\n",
"\n",
"DataAccessLayer.changeEDEXHost(\"edex-cloud.unidata.ucar.edu\")\n",
"request = DataAccessLayer.newDataRequest()\n",
"request.setDatatype(\"satellite\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Available Satellite Sectors and Products"
]
},
{
"cell_type": "code",
"execution_count": 81,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Available sectors and products\n",
"\n",
"Alaska National:\n",
" - Imager 11 micron IR\n",
" - Imager 6.7-6.5 micron IR (WV)\n",
" - Imager Visible\n",
" - Percent of Normal TPW\n",
" - Rain fall rate\n",
" - Sounder Based Derived Precipitable Water (PW)\n",
"Alaska Regional:\n",
" - Imager 11 micron IR\n",
" - Imager 3.9 micron IR\n",
" - Imager 6.7-6.5 micron IR (WV)\n",
" - Imager Visible\n",
"East CONUS:\n",
" - Imager 11 micron IR\n",
" - Imager 13 micron (IR)\n",
" - Imager 3.9 micron IR\n",
" - Imager 6.7-6.5 micron IR (WV)\n",
" - Imager Visible\n",
" - Low cloud base imagery\n",
"GOES-East:\n",
" - Imager 11 micron IR\n",
" - Imager 13 micron IR\n",
" - Imager 3.5-4.0 micron IR (Fog)\n",
" - Imager 6.7-6.5 micron IR (WV)\n",
" - Imager Visible\n",
"GOES-East-West:\n",
" - Imager 11 micron IR\n",
" - Imager 13 micron IR\n",
" - Imager 3.5-4.0 micron IR (Fog)\n",
" - Imager 6.7-6.5 micron IR (WV)\n",
" - Imager Visible\n",
"GOES-Sounder:\n",
" - CAPE\n",
" - Sounder Based Derived Lifted Index (LI)\n",
" - Sounder Based Derived Precipitable Water (PW)\n",
" - Sounder Based Derived Surface Skin Temp (SFC Skin)\n",
" - Sounder Based Total Column Ozone\n",
"GOES-West:\n",
" - Imager 11 micron IR\n",
" - Imager 13 micron IR\n",
" - Imager 3.5-4.0 micron IR (Fog)\n",
" - Imager 6.7-6.5 micron IR (WV)\n",
" - Imager Visible\n",
"Global:\n",
" - Imager 11 micron IR\n",
" - Imager 6.7-6.5 micron IR (WV)\n",
"Hawaii National:\n",
" - Gridded Cloud Amount\n",
" - Gridded Cloud Top Pressure or Height\n",
" - Imager 11 micron IR\n",
" - Imager 6.7-6.5 micron IR (WV)\n",
" - Imager Visible\n",
" - Percent of Normal TPW\n",
" - Rain fall rate\n",
" - Sounder 11.03 micron imagery\n",
" - Sounder 14.06 micron imagery\n",
" - Sounder 3.98 micron imagery\n",
" - Sounder 4.45 micron imagery\n",
" - Sounder 6.51 micron imagery\n",
" - Sounder 7.02 micron imagery\n",
" - Sounder 7.43 micron imagery\n",
" - Sounder Based Derived Lifted Index (LI)\n",
" - Sounder Based Derived Precipitable Water (PW)\n",
" - Sounder Based Derived Surface Skin Temp (SFC Skin)\n",
" - Sounder Visible imagery\n",
"Hawaii Regional:\n",
" - Imager 11 micron IR\n",
" - Imager 13 micron (IR)\n",
" - Imager 3.9 micron IR\n",
" - Imager 6.7-6.5 micron IR (WV)\n",
" - Imager Visible\n",
"Mollweide:\n",
" - Imager 11 micron IR\n",
" - Imager 6.7-6.5 micron IR (WV)\n",
"NEXRCOMP:\n",
" - DHR\n",
" - DVL\n",
" - EET\n",
" - HHC\n",
" - N0R\n",
" - N1P\n",
" - NTP\n",
"NH Composite - Meteosat-GOES E-GOES W-GMS:\n",
" - Imager 11 micron IR\n",
" - Imager 6.7-6.5 micron IR (WV)\n",
" - Imager Visible\n",
"Northern Hemisphere Composite:\n",
" - Imager 11 micron IR\n",
" - Imager 6.7-6.5 micron IR (WV)\n",
" - Imager Visible\n",
"Puerto Rico National:\n",
" - Imager 11 micron IR\n",
" - Imager 6.7-6.5 micron IR (WV)\n",
" - Imager Visible\n",
" - Percent of Normal TPW\n",
" - Rain fall rate\n",
" - Sounder Based Derived Precipitable Water (PW)\n",
"Puerto Rico Regional:\n",
" - Imager 11 micron IR\n",
" - Imager 13 micron (IR)\n",
" - Imager 3.9 micron IR\n",
" - Imager 6.7-6.5 micron IR (WV)\n",
" - Imager Visible\n",
"Supernational:\n",
" - Gridded Cloud Amount\n",
" - Gridded Cloud Top Pressure or Height\n",
" - Imager 11 micron IR\n",
" - Imager 6.7-6.5 micron IR (WV)\n",
" - Imager Visible\n",
" - Percent of Normal TPW\n",
" - Rain fall rate\n",
" - Sounder Based Derived Lifted Index (LI)\n",
" - Sounder Based Derived Precipitable Water (PW)\n",
" - Sounder Based Derived Surface Skin Temp (SFC Skin)\n",
"West CONUS:\n",
" - Imager 11 micron IR\n",
" - Imager 13 micron (IR)\n",
" - Imager 3.9 micron IR\n",
" - Imager 6.7-6.5 micron IR (WV)\n",
" - Imager Visible\n",
" - Low cloud base imagery\n",
" - Sounder 11.03 micron imagery\n",
" - Sounder 14.06 micron imagery\n",
" - Sounder 3.98 micron imagery\n",
" - Sounder 4.45 micron imagery\n",
" - Sounder 6.51 micron imagery\n",
" - Sounder 7.02 micron imagery\n",
" - Sounder 7.43 micron imagery\n",
" - Sounder Visible imagery\n"
]
}
],
"source": [
"availableSectors = DataAccessLayer.getAvailableLocationNames(request)\n",
"availableSectors.sort()\n",
"\n",
"print(\"\\nAvailable sectors and products\\n\")\n",
"for sect in availableSectors:\n",
" request.setLocationNames(sect)\n",
" availableProducts = DataAccessLayer.getAvailableParameters(request)\n",
" availableProducts.sort()\n",
" print(sect + \":\")\n",
" for prod in availableProducts:\n",
" print(\" - \"+prod)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Plot Global Water Vapor Composite"
]
},
{
"cell_type": "code",
"execution_count": 82,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Found 96 available times\n",
" 2017-01-23 00:00:00\n",
" to\n",
" 2017-02-03 21:00:00\n",
"Using 2017-02-03 21:00:00 (2hr 3m ago)\n"
]
}
],
"source": [
"request.setLocationNames(\"Global\")\n",
"availableProducts = DataAccessLayer.getAvailableParameters(request)\n",
"availableProducts.sort()\n",
"request.setParameters(availableProducts[0])\n",
"\n",
"utc = datetime.datetime.utcnow()\n",
"times = DataAccessLayer.getAvailableTimes(request)\n",
"hourdiff = utc - datetime.datetime.strptime(str(times[-1]),'%Y-%m-%d %H:%M:%S')\n",
"hours,days = hourdiff.seconds/3600,hourdiff.days\n",
"minute = str((hourdiff.seconds - (3600 * hours)) / 60)\n",
"offsetStr = ''\n",
"if hours > 0:\n",
" offsetStr += str(hours) + \"hr \"\n",
"offsetStr += str(minute) + \"m ago\"\n",
"if days > 1:\n",
" offsetStr = str(days) + \" days ago\"\n",
"\n",
"print(\"Found \"+ str(len(times)) +\" available times\")\n",
"print(\" \"+str(times[0]) + \"\\n to\\n \" + str(times[-1]))\n",
"print(\"Using \"+str(times[-1]) + \" (\"+offsetStr+\")\")"
]
},
{
"cell_type": "code",
"execution_count": 83,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"grid size (1024, 2048)\n",
"grid extent [-179.91191, 179.99982, -89.977936, 89.890022]\n"
]
}
],
"source": [
"response = DataAccessLayer.getGridData(request, [times[-1]])\n",
"grid = response[0]\n",
"data = grid.getRawData()\n",
"lons,lats = grid.getLatLonCoords()\n",
"bbox = [lons.min(), lons.max(), lats.min(), lats.max()]\n",
"\n",
"print(\"grid size \" + str(data.shape))\n",
"print(\"grid extent \" + str(list(bbox)))"
]
},
{
"cell_type": "code",
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"execution_count": 10,
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"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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"text/plain": [
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"<matplotlib.figure.Figure at 0x10a61d190>"
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]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"def make_map(bbox, projection=ccrs.PlateCarree()):\n",
" fig, ax = plt.subplots(figsize=(18,14),\n",
" subplot_kw=dict(projection=projection))\n",
" ax.set_extent(bbox)\n",
" ax.coastlines(resolution='50m')\n",
" gl = ax.gridlines(draw_labels=True)\n",
" gl.xlabels_top = gl.ylabels_right = False\n",
" gl.xformatter = LONGITUDE_FORMATTER\n",
" gl.yformatter = LATITUDE_FORMATTER\n",
" return fig, ax\n",
"\n",
"fig, ax = make_map(bbox=bbox)\n",
"# State boundaries\n",
"states = cfeat.NaturalEarthFeature(category='cultural',\n",
" name='admin_1_states_provinces_lines',\n",
" scale='50m', facecolor='none')\n",
"ax.add_feature(states, linestyle=':')\n",
"cs = ax.pcolormesh(lons, lats, data, cmap='Greys_r')\n",
"cbar = fig.colorbar(cs, shrink=0.9, orientation='horizontal')\n",
"cbar.set_label(str(grid.getLocationName())+\" \" \\\n",
" +str(grid.getParameter())+\" \" \\\n",
" +str(grid.getDataTime().getRefTime()))\n",
"plt.tight_layout()"
]
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},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
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}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
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},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
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