Add reader for GERB high-resolution HDF5 files

satpy/etc/readers/gerb_l2_hr_h5.yaml

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+reader:
+  name: gerb_l2_hr_h5
+  short_name: GERB HR
+  long_name: Meteosat Second Generation Geostationary Earth Radiation Budget L2 High-Resolution
+  description: Reader for the HR product of the Geostationary Earth Radiation Budget instrument
+  status: Beta
+  supports_fsspec: false
+  reader: !!python/name:satpy.readers.yaml_reader.FileYAMLReader
+  sensors: [gerb]
+
+file_types:
+  gerb_l2_hr_h5:
+    file_reader: !!python/name:satpy.readers.gerb_l2_hr_h5.GERB_HR_FileHandler
+    file_patterns: ['{sensor_name}_{seviri_name}_L20_HR_SOL_TH_{sensing_time:%Y%m%d_%H%M%S}_{gerb_version}.hdf']
+
+datasets:
+  Solar_Flux:
+    name: Solar Flux
+    sensor: gerb
+    units: W m-2
+    fill_value: -32767
+    standard_name: toa_outgoing_shortwave_flux
+    file_type: gerb_l2_hr_h5
+
+  Thermal_Flux:
+    name: Thermal Flux
+    sensor: gerb
+    units: W m-2
+    fill_value: -32767
+    standard_name: toa_outgoing_longwave_flux
+    file_type: gerb_l2_hr_h5
+
+  Solar_Radiance:
+    name: Solar Radiance
+    sensor: gerb
+    units: W m-2 sr-1
+    fill_value: -32767
+    file_type: gerb_l2_hr_h5
+
+  Thermal_Radiance:
+    name: Thermal Radiance
+    sensor: gerb
+    units: W m-2 sr-1
+    fill_value: -32767
+    file_type: gerb_l2_hr_h5

satpy/readers/gerb_l2_hr_h5.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# Copyright (c) 2023
+#
+# 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/>.
+
+
+"""GERB L2 HR HDF5 reader.
+
+A reader for the Top of Atmosphere outgoing fluxes from the Geostationary Earth Radiation
+Budget instrument aboard the Meteosat Second Generation satellites.
+"""
+
+
+import logging
+from datetime import timedelta
+
+from satpy.readers.hdf5_utils import HDF5FileHandler
+from satpy.resample import get_area_def
+
+LOG = logging.getLogger(__name__)
+
+
+def gerb_get_dataset(ds, ds_info):
+    """
+    Load a GERB dataset in memory from a HDF5 file or HDF5FileHandler.
+
+    The routine takes into account the quantisation factor and fill values.
+    """
+    ds_attrs = ds.attrs
+    ds_fill = ds_info['fill_value']
+    fill_mask = ds != ds_fill
+    if 'Quantisation Factor' in ds_attrs and 'Unit' in ds_attrs:
+        ds = ds*ds_attrs['Quantisation Factor']
+    else:
+        ds = ds*1.
+    ds = ds.where(fill_mask)
+    return ds
+
+
+class GERB_HR_FileHandler(HDF5FileHandler):
+    """File handler for GERB L2 High Resolution H5 files."""
+
+    @property
+    def end_time(self):
+        """Get end time."""
+        return self.start_time + timedelta(minutes=15)
+
+    @property
+    def start_time(self):
+        """Get start time."""
+        return self.filename_info['sensing_time']
+
+    def get_dataset(self, ds_id, ds_info):
+        """Read a HDF5 file into an xarray DataArray."""
+        ds_name = ds_id['name']
+        if ds_name not in ['Solar Flux', 'Thermal Flux', 'Solar Radiance', 'Thermal Radiance']:
+            raise KeyError(f"{ds_name} is an unknown dataset for this reader.")
+
+        ds = gerb_get_dataset(self[f'Radiometry/{ds_name}'], ds_info)
+
+        ds.attrs.update({'start_time': self.start_time, 'data_time': self.start_time, 'end_time': self.end_time})
+
+        return ds
+
+    def get_area_def(self, dsid):
+        """Area definition for the GERB product."""
+        ssp_lon = self.file_content["Geolocation/attr/Nominal Satellite Longitude (degrees)"]
+
+        if abs(ssp_lon) < 1e-6:
+            return get_area_def("msg_seviri_fes_9km")
+        elif abs(ssp_lon - 9.5) < 1e-6:
+            return get_area_def("msg_seviri_fes_9km")
+        elif abs(ssp_lon - 45.5) < 1e-6:
+            return get_area_def("msg_seviri_iodc_9km")
+        else:
+            raise ValueError(f"There is no matching grid for SSP longitude {self.ssp_lon}")

satpy/tests/reader_tests/test_gerb_l2_hr_h5.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# Copyright (c) 2018 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/>.
+"""Unit tests for GERB L2 HR HDF5 reader."""
+
+import h5py
+import numpy as np
+import pytest
+
+from satpy import Scene
+
+FNAME = "G4_SEV4_L20_HR_SOL_TH_20190606_130000_V000.hdf"
+
+
+def make_h5_null_string(length):
+    """Make a HDF5 type for a NULL terminated string of fixed length."""
+    dt = h5py.h5t.TypeID.copy(h5py.h5t.C_S1)
+    dt.set_size(7)
+    dt.set_strpad(h5py.h5t.STR_NULLTERM)
+    return dt
+
+
+def write_h5_null_string_att(loc_id, name, s):
+    """Write a NULL terminated string attribute at loc_id."""
+    dt = make_h5_null_string(length=7)
+    name = bytes(name.encode('ascii'))
+    s = bytes(s.encode('ascii'))
+    at = h5py.h5a.create(loc_id, name, dt, h5py.h5s.create(h5py.h5s.SCALAR))
+    at.write(np.array(s, dtype=f'|S{len(s)+1}'))
+
+
+@pytest.fixture(scope="session")
+def gerb_l2_hr_h5_dummy_file(tmp_path_factory):
+    """Create a dummy HDF5 file for the GERB L2 HR product."""
+    filename = tmp_path_factory.mktemp("data") / FNAME
+
+    with h5py.File(filename, 'w') as fid:
+        fid.create_group('/Angles')
+        fid['/Angles/Relative Azimuth'] = np.ones(shape=(1237, 1237), dtype=np.dtype('>i2'))
+        fid['/Angles/Relative Azimuth'].attrs['Quantisation Factor'] = np.array(0.1, dtype='float64')
+        fid['/Angles/Solar Zenith'] = np.ones(shape=(1237, 1237), dtype=np.dtype('>i2'))
+        fid['/Angles/Solar Zenith'].attrs['Quantisation Factor'] = np.array(0.1, dtype='float64')
+        write_h5_null_string_att(fid['/Angles/Relative Azimuth'].id, 'Unit', 'Degree')
+        fid['/Angles/Viewing Azimuth'] = np.ones(shape=(1237, 1237), dtype=np.dtype('>i2'))
+        fid['/Angles/Viewing Azimuth'].attrs['Quantisation Factor'] = np.array(0.1, dtype='float64')
+        write_h5_null_string_att(fid['/Angles/Viewing Azimuth'].id, 'Unit', 'Degree')
+        fid['/Angles/Viewing Zenith'] = np.ones(shape=(1237, 1237), dtype=np.dtype('>i2'))
+        fid['/Angles/Viewing Zenith'].attrs['Quantisation Factor'] = np.array(0.1, dtype='float64')
+        write_h5_null_string_att(fid['/Angles/Viewing Zenith'].id, 'Unit', 'Degree')
+        fid.create_group('/GERB')
+        dt = h5py.h5t.TypeID.copy(h5py.h5t.C_S1)
+        dt.set_size(3)
+        dt.set_strpad(h5py.h5t.STR_NULLTERM)
+        write_h5_null_string_att(fid['/GERB'].id, 'Instrument Identifier', 'G4')
+        fid.create_group('/GGSPS')
+        fid['/GGSPS'].attrs['L1.5 NANRG Product Version'] = np.array(-1, dtype='int32')
+        fid.create_group('/Geolocation')
+        write_h5_null_string_att(fid['/Geolocation'].id, 'Geolocation File Name',
+                                 'G4_SEV4_L20_HR_GEO_20180111_181500_V010.hdf')
+        fid['/Geolocation'].attrs['Nominal Satellite Longitude (degrees)'] = np.array(0.0, dtype='float64')
+        fid.create_group('/Imager')
+        fid['/Imager'].attrs['Instrument Identifier'] = np.array(4, dtype='int32')
+        write_h5_null_string_att(fid['/Imager'].id, 'Type', 'SEVIRI')
+        fid.create_group('/RMIB')
+        fid.create_group('/Radiometry')
+        fid['/Radiometry'].attrs['SEVIRI Radiance Definition Flag'] = np.array(2, dtype='int32')
+        fid['/Radiometry/A Values (per GERB detector cell)'] = np.ones(shape=(256,), dtype=np.dtype('>f8'))
+        fid['/Radiometry/C Values (per GERB detector cell)'] = np.ones(shape=(256,), dtype=np.dtype('>f8'))
+        fid['/Radiometry/Longwave Correction'] = np.ones(shape=(1237, 1237), dtype=np.dtype('>i2'))
+        fid['/Radiometry/Longwave Correction'].attrs['Offset'] = np.array(1.0, dtype='float64')
+        fid['/Radiometry/Longwave Correction'].attrs['Quantisation Factor'] = np.array(0.005, dtype='float64')
+        fid['/Radiometry/Shortwave Correction'] = np.ones(shape=(1237, 1237), dtype=np.dtype('>i2'))
+        fid['/Radiometry/Shortwave Correction'].attrs['Offset'] = np.array(1.0, dtype='float64')
+        fid['/Radiometry/Shortwave Correction'].attrs['Quantisation Factor'] = np.array(0.005, dtype='float64')
+        fid['/Radiometry/Solar Flux'] = np.ones(shape=(1237, 1237), dtype=np.dtype('>i2'))
+        fid['/Radiometry/Solar Flux'].attrs['Quantisation Factor'] = np.array(0.25, dtype='float64')
+        write_h5_null_string_att(fid['/Radiometry/Solar Flux'].id, 'Unit', 'Watt per square meter')
+        fid['/Radiometry/Solar Radiance'] = np.ones(shape=(1237, 1237), dtype=np.dtype('>i2'))
+        fid['/Radiometry/Solar Radiance'].attrs['Quantisation Factor'] = np.array(0.05, dtype='float64')
+        write_h5_null_string_att(fid['/Radiometry/Solar Radiance'].id, 'Unit', 'Watt per square meter per steradian')
+        fid['/Radiometry/Thermal Flux'] = np.ones(shape=(1237, 1237), dtype=np.dtype('>i2'))
+        fid['/Radiometry/Thermal Flux'].attrs['Quantisation Factor'] = np.array(0.25, dtype='float64')
+        write_h5_null_string_att(fid['/Radiometry/Thermal Flux'].id, 'Unit', 'Watt per square meter')
+        fid['/Radiometry/Thermal Radiance'] = np.ones(shape=(1237, 1237), dtype=np.dtype('>i2'))
+        fid['/Radiometry/Thermal Radiance'].attrs['Quantisation Factor'] = np.array(0.05, dtype='float64')
+        write_h5_null_string_att(fid['/Radiometry/Thermal Radiance'].id, 'Unit', 'Watt per square meter per steradian')
+        fid.create_group('/Scene Identification')
+        write_h5_null_string_att(fid['/Scene Identification'].id,
+                                 'Solar Angular Dependency Models Set Version', 'CERES_TRMM.1')
+        write_h5_null_string_att(fid['/Scene Identification'].id,
+                                 'Thermal Angular Dependency Models Set Version', 'RMIB.3')
+        fid['/Scene Identification/Cloud Cover'] = np.ones(shape=(1237, 1237), dtype=np.dtype('uint8'))
+        fid['/Scene Identification/Cloud Cover'].attrs['Quantisation Factor'] = np.array(0.01, dtype='float64')
+        write_h5_null_string_att(fid['/Scene Identification/Cloud Cover'].id, 'Unit', 'Percent')
+        fid['/Scene Identification/Cloud Optical Depth (logarithm)'] = \
+            np.ones(shape=(1237, 1237), dtype=np.dtype('>i2'))
+        fid['/Scene Identification/Cloud Optical Depth (logarithm)'].attrs['Quantisation Factor'] = \
+            np.array(0.00025, dtype='float64')
+        fid['/Scene Identification/Cloud Phase'] = np.ones(shape=(1237, 1237), dtype=np.dtype('uint8'))
+        fid['/Scene Identification/Cloud Phase'].attrs['Quantisation Factor'] = np.array(0.01, dtype='float64')
+        write_h5_null_string_att(fid['/Scene Identification/Cloud Phase'].id, 'Unit',
+                                 'Percent (Water=0%,Mixed,Ice=100%)')
+        fid.create_group('/Times')
+        fid['/Times/Time (per row)'] = np.ones(shape=(1237,), dtype=np.dtype('|S22'))
+
+    return filename
+
+
+@pytest.mark.parametrize("name", ["Solar Flux", "Thermal Flux", "Solar Radiance", "Thermal Radiance"])
+def test_dataset_load(gerb_l2_hr_h5_dummy_file, name):
+    """Test loading the solar flux component."""
+    scene = Scene(reader='gerb_l2_hr_h5', filenames=[gerb_l2_hr_h5_dummy_file])
+    scene.load([name])
+    assert scene[name].shape == (1237, 1237)
+    assert np.nanmax((scene[name].to_numpy().flatten() - 0.25)) < 1e-6