#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2016-2019 Satpy developers
#
# This file is part of satpy.
#
# satpy is free software: you can redistribute it and/or modify it under the
# terms of the GNU General Public License as published by the Free Software
# Foundation, either version 3 of the License, or (at your option) any later
# version.
#
# satpy is distributed in the hope that it will be useful, but WITHOUT ANY
# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
# A PARTICULAR PURPOSE. See the GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License along with
# satpy. If not, see <http://www.gnu.org/licenses/>.
"""Advance Baseline Imager reader for the Level 1b format.
The files read by this reader are described in the official PUG document:
https://www.goes-r.gov/users/docs/PUG-L1b-vol3.pdf
"""
import logging
import numpy as np
from satpy.readers.abi_base import NC_ABI_BASE
logger = logging.getLogger(__name__)
[docs]class NC_ABI_L1B(NC_ABI_BASE):
"""File reader for individual ABI L1B NetCDF4 files."""
[docs] def get_dataset(self, key, info):
"""Load a dataset."""
logger.debug('Reading in get_dataset %s.', key['name'])
# For raw cal, don't apply scale and offset, return raw file counts
if key['calibration'] == 'counts':
radiances = self.nc['Rad'].copy()
else:
radiances = self['Rad']
# mapping of calibration types to calibration functions
cal_dictionary = {
'reflectance': self._vis_calibrate,
'brightness_temperature': self._ir_calibrate,
'radiance': self._rad_calibrate,
'counts': self._raw_calibrate,
}
try:
func = cal_dictionary[key['calibration']]
res = func(radiances)
except KeyError:
raise ValueError("Unknown calibration '{}'".format(key['calibration']))
# convert to satpy standard units
if res.attrs['units'] == '1' and key['calibration'] != 'counts':
res *= 100
res.attrs['units'] = '%'
self._adjust_attrs(res, key)
return res
def _adjust_attrs(self, data, key):
data.attrs.update({'platform_name': self.platform_name,
'sensor': self.sensor})
# Add orbital parameters
projection = self.nc["goes_imager_projection"]
data.attrs['orbital_parameters'] = {
'projection_longitude': float(projection.attrs['longitude_of_projection_origin']),
'projection_latitude': float(projection.attrs['latitude_of_projection_origin']),
'projection_altitude': float(projection.attrs['perspective_point_height']),
'satellite_nominal_latitude': float(self['nominal_satellite_subpoint_lat']),
'satellite_nominal_longitude': float(self['nominal_satellite_subpoint_lon']),
'satellite_nominal_altitude': float(self['nominal_satellite_height']) * 1000.,
'yaw_flip': bool(self['yaw_flip_flag']),
}
data.attrs.update(key.to_dict())
# remove attributes that could be confusing later
# if calibration type is raw counts, we leave them in
if key['calibration'] != 'counts':
data.attrs.pop('_FillValue', None)
data.attrs.pop('scale_factor', None)
data.attrs.pop('add_offset', None)
data.attrs.pop('_Unsigned', None)
data.attrs.pop('ancillary_variables', None) # Can't currently load DQF
# although we could compute these, we'd have to update in calibration
data.attrs.pop('valid_range', None)
# add in information from the filename that may be useful to the user
for attr in ('observation_type', 'scene_abbr', 'scan_mode', 'platform_shortname', 'suffix'):
if attr in self.filename_info:
data.attrs[attr] = self.filename_info[attr]
# copy global attributes to metadata
for attr in ('scene_id', 'orbital_slot', 'instrument_ID', 'production_site', 'timeline_ID'):
data.attrs[attr] = self.nc.attrs.get(attr)
# only include these if they are present
for attr in ('fusion_args',):
if attr in self.nc.attrs:
data.attrs[attr] = self.nc.attrs[attr]
def _rad_calibrate(self, data):
"""Calibrate any channel to radiances.
This no-op method is just to keep the flow consistent -
each valid cal type results in a calibration method call
"""
res = data
res.attrs = data.attrs
return res
def _raw_calibrate(self, data):
"""Calibrate any channel to raw counts.
Useful for cases where a copy requires no calibration.
"""
res = data
res.attrs = data.attrs
res.attrs['units'] = '1'
res.attrs['long_name'] = 'Raw Counts'
res.attrs['standard_name'] = 'counts'
return res
def _vis_calibrate(self, data):
"""Calibrate visible channels to reflectance."""
solar_irradiance = self['esun']
esd = self["earth_sun_distance_anomaly_in_AU"].astype(float)
factor = np.pi * esd * esd / solar_irradiance
res = data * factor
res.attrs = data.attrs
res.attrs['units'] = '1'
res.attrs['long_name'] = 'Bidirectional Reflectance'
res.attrs['standard_name'] = 'toa_bidirectional_reflectance'
return res
def _ir_calibrate(self, data):
"""Calibrate IR channels to BT."""
fk1 = float(self["planck_fk1"])
fk2 = float(self["planck_fk2"])
bc1 = float(self["planck_bc1"])
bc2 = float(self["planck_bc2"])
res = (fk2 / np.log(fk1 / data + 1) - bc1) / bc2
res.attrs = data.attrs
res.attrs['units'] = 'K'
res.attrs['long_name'] = 'Brightness Temperature'
res.attrs['standard_name'] = 'toa_brightness_temperature'
return res