GOES¶

This notebook shows how to download observations from the currently active GOES geo-stationary satellites. The GOES products are available in three views: 1. CONUS: Fixed view of the continental united states. 2. Full disk: The full disk, i.e. covering \(-90\ ^\circ\) to \(90\ ^\circ\) in latitude. 3. Meso-scale sector: Dynamic, high-resolution observations of storms and other regions of interest.

GOES 16¶

Here, we will download level 1b radiances from all channels and display them.

[1]:

%load_ext autoreload
%autoreload 2
import matplotlib.pyplot
import numpy as np
from datetime import datetime
from pansat.products.satellite.goes import goes_16_l1b_radiances_all_conus

[2]:

t_0 = datetime(2020, 8, 27, 17, 10)
t_1 = datetime(2020, 8, 27, 17, 15)
files = goes_16_l1b_radiances_all_conus.download(t_0, t_1)

[3]:

from satpy import Scene
from glob import glob

scn = Scene(reader='abi_l1b', filenames=files)
scn.load(['true_color'])
small_scn = scn.resample(scn.min_area(), resampler='native')
small_scn["true_color_small"] = small_scn["true_color"][:, ::8, ::8]
small_scn.save_dataset('true_color_small', filename='hurricane_laura_16.png')

satpy.scene (WARNING   ) :: The following datasets were not created and may require resampling to be generated: DataID(name='true_color')
/home/simon/build/anaconda3/lib/python3.7/site-packages/satpy/node.py:105: UserWarning: Attribute access to DataIDs is deprecated, use key access instead.
  return self.name == other.name
/home/simon/build/anaconda3/lib/python3.7/site-packages/dask/core.py:119: RuntimeWarning: invalid value encountered in greater
  return func(*args2)
/home/simon/build/anaconda3/lib/python3.7/site-packages/dask/core.py:119: RuntimeWarning: invalid value encountered in log
  return func(*args2)
/home/simon/build/anaconda3/lib/python3.7/site-packages/dask/core.py:119: RuntimeWarning: invalid value encountered in less
  return func(*args2)
/home/simon/build/anaconda3/lib/python3.7/site-packages/satpy/resample.py:925: RuntimeWarning: Mean of empty slice
  data_mean = np.nanmean(data.reshape(new_shape), axis=(1, 3))
/home/simon/build/anaconda3/lib/python3.7/site-packages/satpy/composites/__init__.py:836: RuntimeWarning: Mean of empty slice
  data_mean = np.nanmean(av_data.reshape(new_shape), axis=(1, 3))
/home/simon/build/anaconda3/lib/python3.7/site-packages/dask/core.py:119: RuntimeWarning: invalid value encountered in greater_equal
  return func(*args2)

[4]:

from PIL import Image
laura = Image.open("hurricane_laura_16.png")
laura

[4]:

../../_images/notebooks_products_goes_5_0.png

GOES 17¶

[5]:

from pansat.products.satellite.goes import goes_17_l1b_radiances_all_conus
t_0 = datetime(2020, 8, 27, 17, 10)
t_1 = datetime(2020, 8, 27, 17, 15)
files = goes_17_l1b_radiances_all_conus.download(t_0, t_1)

[6]:

scn = Scene(reader='abi_l1b', filenames=files)
scn.load(['true_color'])

small_scn = scn.resample(scn.min_area(), resampler='native')
small_scn["true_color_small"] = small_scn["true_color"][:, ::8, ::8]
small_scn.save_dataset('true_color_small', filename='goes_17.png')

satpy.scene (WARNING   ) :: The following datasets were not created and may require resampling to be generated: DataID(name='true_color')
/home/simon/build/anaconda3/lib/python3.7/site-packages/satpy/node.py:105: UserWarning: Attribute access to DataIDs is deprecated, use key access instead.
  return self.name == other.name
/home/simon/build/anaconda3/lib/python3.7/site-packages/dask/core.py:119: RuntimeWarning: invalid value encountered in log
  return func(*args2)

[7]:

from PIL import Image
laura = Image.open("goes_17.png")
laura

[7]:

../../_images/notebooks_products_goes_9_0.png