satpy.readers.olci_nc module

Sentinel-3 OLCI reader.

This reader supports an optional argument to choose the ‘engine’ for reading OLCI netCDF4 files. By default, this reader uses the default xarray choice of engine, as defined in the xarray.open_dataset() documentation`.

As an alternative, the user may wish to use the ‘h5netcdf’ engine, but that is not default as it typically prints many non-fatal but confusing error messages to the terminal. To choose between engines the user can do as follows for the default:

scn = Scene(filenames=my_files, reader='olci_l1b')

or as follows for the h5netcdf engine:

scn = Scene(filenames=my_files,
            reader='olci_l1b', reader_kwargs={'engine': 'h5netcdf'})

References

class satpy.readers.olci_nc.BitFlags(value)[source]

Bases: object

Manipulate flags stored bitwise.

Init the flags.

flag_list = ['INVALID', 'WATER', 'LAND', 'CLOUD', 'SNOW_ICE', 'INLAND_WATER', 'TIDAL', 'COSMETIC', 'SUSPECT', 'HISOLZEN', 'SATURATED', 'MEGLINT', 'HIGHGLINT', 'WHITECAPS', 'ADJAC', 'WV_FAIL', 'PAR_FAIL', 'AC_FAIL', 'OC4ME_FAIL', 'OCNN_FAIL', 'Extra_1', 'KDM_FAIL', 'Extra_2', 'CLOUD_AMBIGUOUS', 'CLOUD_MARGIN', 'BPAC_ON', 'WHITE_SCATT', 'LOWRW', 'HIGHRW']
meaning = {'AC_FAIL': 17, 'ADJAC': 14, 'BPAC_ON': 25, 'CLOUD': 3, 'CLOUD_AMBIGUOUS': 23, 'CLOUD_MARGIN': 24, 'COSMETIC': 7, 'Extra_1': 20, 'Extra_2': 22, 'HIGHGLINT': 12, 'HIGHRW': 28, 'HISOLZEN': 9, 'INLAND_WATER': 5, 'INVALID': 0, 'KDM_FAIL': 21, 'LAND': 2, 'LOWRW': 27, 'MEGLINT': 11, 'OC4ME_FAIL': 18, 'OCNN_FAIL': 19, 'PAR_FAIL': 16, 'SATURATED': 10, 'SNOW_ICE': 4, 'SUSPECT': 8, 'TIDAL': 6, 'WATER': 1, 'WHITECAPS': 13, 'WHITE_SCATT': 26, 'WV_FAIL': 15}
class satpy.readers.olci_nc.NCOLCI1B(filename, filename_info, filetype_info, cal, engine=None)[source]

Bases: NCOLCIChannelBase

File handler for OLCI l1b.

Init the file handler.

get_dataset(key, info)[source]

Load a dataset.

class satpy.readers.olci_nc.NCOLCI2(filename, filename_info, filetype_info, engine=None)[source]

Bases: NCOLCIChannelBase

File handler for OLCI l2.

Init the file handler.

get_dataset(key, info)[source]

Load a dataset.

getbitmask(wqsf, items=None)[source]

Get the bitmask.

class satpy.readers.olci_nc.NCOLCIAngles(filename, filename_info, filetype_info, engine=None)[source]

Bases: NCOLCILowResData

File handler for the OLCI angles.

Init the file handler.

datasets = {'satellite_azimuth_angle': 'OAA', 'satellite_zenith_angle': 'OZA', 'solar_azimuth_angle': 'SAA', 'solar_zenith_angle': 'SZA'}
get_dataset(key, info)[source]

Load a dataset.

property satellite_angles

Return the satellite angles.

property sun_angles

Return the sun angles.

class satpy.readers.olci_nc.NCOLCIBase(filename, filename_info, filetype_info, engine=None)[source]

Bases: BaseFileHandler

The OLCI reader base.

Init the olci reader base.

cols_name = 'columns'
property end_time

End time property.

get_dataset(key, info)[source]

Load a dataset.

property nc

Get the nc xr dataset.

rows_name = 'rows'
property start_time

Start time property.

class satpy.readers.olci_nc.NCOLCICal(filename, filename_info, filetype_info, engine=None)[source]

Bases: NCOLCIBase

Dummy class for calibration.

Init the olci reader base.

class satpy.readers.olci_nc.NCOLCIChannelBase(filename, filename_info, filetype_info, engine=None)[source]

Bases: NCOLCIBase

Base class for channel reading.

Init the file handler.

class satpy.readers.olci_nc.NCOLCIGeo(filename, filename_info, filetype_info, engine=None)[source]

Bases: NCOLCIBase

Dummy class for navigation.

Init the olci reader base.

class satpy.readers.olci_nc.NCOLCILowResData(filename, filename_info, filetype_info, engine=None)[source]

Bases: NCOLCIBase

Handler for low resolution data.

Init the file handler.

cols_name = 'tie_columns'
rows_name = 'tie_rows'
class satpy.readers.olci_nc.NCOLCIMeteo(filename, filename_info, filetype_info, engine=None)[source]

Bases: NCOLCILowResData

File handler for the OLCI meteo data.

Init the file handler.

datasets = ['humidity', 'sea_level_pressure', 'total_columnar_water_vapour', 'total_ozone']
get_dataset(key, info)[source]

Load a dataset.