1. pytroll-examples
  2. satpy

AVHRR GAC Reader Introduction

Satpy uses pygac to read and calibrate AVHRR GAC (Global Area Coverage) data. A reader for LAC (Local Area Coverage) data is under development. Check out https://github.com/pytroll/pygac/pull/5 if you are interested in contributing to the project.

Further Reading: https://www.avl.class.noaa.gov/release/data_available/avhrr/index.htm

Supported Files

AVHRR data in NOAA GAC format. Example filename: NSS.GHRR.NP.D15361.S0121.E0315.B3547172.SV

Quickstart with AVHRR GAC data from NOAA-14

In [ ]:
from datetime import datetime
from satpy.scene import Scene

scn = Scene(sensor="avhrr-2",
            start_time=datetime(1995, 2, 24, 9, 40),
            end_time=datetime(1995, 2, 24, 9, 42),
            base_dir='/home/a001673/usr/src/cci_geolocation/data',
            reader="avhrr_l1b_gaclac",
            reader_kwargs={'tle_dir': '/path/to/tle/',
                           'tle_name': 'TLE_%(satname)s.txt'})
In [ ]:
composite = 'overview'
scn.load([composite])
scn.show(composite)

Note that you have to specify location and format of the so called Two-Line-Elements (TLE) via reader_kwargs. Some NOAA-16 TLEs are available in pygac's github repository. Historical TLEs can be obtained from https://www.celestrak.com/ and have the following format:

1 23455U 94089A   01122.93455091  .00000622  00000-0  36103-3 0  7210
2 23455  99.1771 113.3063 0008405 277.6106  82.4106 14.12671703326608
1 23455U 94089A   01326.97611660  .00000739  00000-0  42245-3 0  9806
2 23455  99.1886 322.4670 0009980  66.2863 293.9354 14.12871991355419
etc

For more keyword arguments checkout out the reader documentation.

Reading Individual Datasets

Of course you can also readout the individual channels and ancillary datasets directly. Here is an example with NOAA-19 data:

In [1]:
%matplotlib inline
In [ ]:
import satpy

# Channel set for KLM satellites. For POD satellites the channels are
# ['1', '2', '3', '4', '5'].
channels = ['1', '2', '3a', '3b', '4', '5']

# Select some ancillary datasets (there are more datasets available, 
# see satpy/etc/readers/avhrr_l1b_gaclac.yaml)
ancillary = ['solar_zenith_angle',
             'sensor_zenith_angle',
             'latitude',
             'longitude'] 

scene = satpy.Scene(filenames=['NSS.GHRR.NP.D15361.S0121.E0315.B3547172.SV'], 
                    reader='avhrr_l1b_gaclac', 
                    reader_kwargs={'tle_dir': 'tle/',
                                   'tle_name': 'TLE_%(satname)s.txt'})
scene.load(channels + ancillary)
In [3]:
scene['4']
Out[3]:
<xarray.DataArray 'array-d416e9b022847a2d5f370401d47356d7' (y: 13760, x: 409)>
dask.array<array, shape=(13760, 409), dtype=float64, chunksize=(13760, 409)>
Coordinates:
    acq_time  (y) datetime64[ns] 2015-12-27T01:21:08.285000 ... 2015-12-27T03:15:47.785000
Dimensions without coordinates: y, x
Attributes:
    orbital_parameters:   {'tle': ('1 33591U 09005A   15360.91031674  .000001...
    platform_name:        noaa19
    orbit_number:         35471
    file_type:            gac_lac_l1b
    calibration:          brightness_temperature
    wavelength:           (10.3, 10.8, 11.3)
    name:                 4
    standard_name:        toa_brightness_temperature
    coordinates:          ('longitude', 'latitude')
    polarization:         None
    modifiers:            ()
    units:                K
    level:                None
    midnight_scanline:    None
    resolution:           1050
    sensor:               avhrr-3
    missing_scanlines:    [    1     2     3     4     5     6     7     8   ...
    start_time:           2015-12-27 01:21:08.285000
    end_time:             2015-12-27 03:15:47.785000
    area:                 Shape: (13760, 409)\nLons: <xarray.DataArray 'array...
    ancillary_variables:  []
In [4]:
import matplotlib.pyplot as plt

fig, (ax1, ax2) = plt.subplots(ncols=2, figsize=(3, 20))
ax1.imshow(scene['4'])
ax2.imshow(scene['solar_zenith_angle'])
plt.show()