satpy.readers.ami_l1b module

Advanced Meteorological Imager reader for the Level 1b NetCDF4 format.

class satpy.readers.ami_l1b.AMIL1bNetCDF(filename, filename_info, filetype_info, calib_mode='PYSPECTRAL', allow_conditional_pixels=False, user_calibration=None, clip_negative_radiances=None)

Bases: BaseFileHandler

Base reader for AMI L1B NetCDF4 files.

AMI data contains GSICS adjustment factors for the IR bands. By default, these are not applied. If you wish to apply them then you must set the calibration mode appropriately:

import satpy
import glob

filenames = glob.glob('*FLDK*.dat')
scene = satpy.Scene(filenames,
                    reader='ahi_hsd',
                    reader_kwargs={'calib_mode': 'gsics'})
scene.load(['B13'])

In addition, the GSICS website (and other sources) also supply radiance correction coefficients like so:

radiance_corr = (radiance_orig - corr_offset) / corr_slope

If you wish to supply such coefficients, pass ‘user_calibration’ and a dictionary containing per-channel slopes and offsets as a reader_kwarg:

user_calibration={'chan': {'slope': slope, 'offset': offset}}

If you do not have coefficients for a particular band, then by default the slope will be set to 1 .and the offset to 0.:

import satpy
import glob

# Load bands 7, 14 and 15, but we only have coefs for 7+14
calib_dict = {'WV063': {'slope': 0.99, 'offset': 0.002},
              'IR087': {'slope': 1.02, 'offset': -0.18}}

filenames = glob.glob('*.nc')
scene = satpy.Scene(filenames,
                    reader='ami_l1b',
                    reader_kwargs={'user_calibration': calib_dict,
                                   'calib_mode': 'file')
# IR133 will not have radiance correction applied.
scene.load(['WV063', 'IR087', 'IR133'])

By default these updated coefficients are not used. In most cases, setting calib_mode to file is required in order to use external coefficients.

Open the NetCDF file with xarray and prepare the Dataset for reading.

_apply_gsics_rad_correction(data)

Retrieve GSICS factors from L1 file and apply to radiance.

_apply_user_rad_correction(data)

Retrieve user-supplied radiance correction and apply.

_calibrate_ir(dataset_id, data)

Calibrate radiance data to BTs using either pyspectral or in-file coefficients.

_clip_negative_radiance(data, gain, offset)

If requested, clip negative radiance from Rad DataArray.

property end_time

Get observation end time.

get_area_def(dsid)

Get area definition for this file.

get_dataset(dataset_id, ds_info)

Load a dataset as a xarray DataArray.

get_orbital_parameters()

Collect orbital parameters for this file.

property start_time

Get observation start time.