How to read cloud products from NWCSAF software. (separate document?)
Satpy supports reading and loading data from many input file formats and schemes. The ~satpy.scene.Scene object provides a simple interface around all the complexity of these various formats through its load method. The following sections describe the different way data can be loaded, requested, or added to a Scene object.
To get a list of available readers use the available_readers function. By default, it returns the names of available readers. To return additional reader information use `available_readers(as_dict=True)`:
>>> from satpy import available_readers
>>> available_readers()Coming soon...
Datasets in Satpy are identified by certain pieces of metadata set during data loading. These include name, wavelength, calibration, resolution, polarization, and modifiers. Normally, once a Scene is created requesting datasets by name or wavelength is all that is needed:
>>> from satpy import Scene
>>> scn = Scene(reader="seviri_l1b_hrit", filenames=filenames)
>>> scn.load([0.6, 0.8, 10.8])
>>> scn.load(['IR_120', 'IR_134'])However, in many cases datasets are available in multiple spatial resolutions, multiple calibrations (brightness_temperature, reflectance, radiance, etc), multiple polarizations, or have corrections or other modifiers already applied to them. By default Satpy will provide the version of the dataset with the highest resolution and the highest level of calibration (brightness temperature or reflectance over radiance). It is also possible to request one of these exact versions of a dataset by using the ~satpy.dataset.DataQuery class:
>>> from satpy import DataQuery
>>> my_channel_id = DataQuery(name='IR_016', calibration='radiance')
>>> scn.load([my_channel_id])
>>> print(scn['IR_016'])Or request multiple datasets at a specific calibration, resolution, or polarization:
>>> scn.load([0.6, 0.8], resolution=1000)Or multiple calibrations:
>>> scn.load([0.6, 10.8], calibrations=['brightness_temperature', 'radiance'])In the above case Satpy will load whatever dataset is available and matches the specified parameters. So the above load call would load the 0.6 (a visible/reflectance band) radiance data and 10.8 (an IR band) brightness temperature data.
For geostationary satellites that have the individual channel data separated to several files (segments) the missing segments are padded by default to full disk area. This is made to simplify caching of resampling look-up tables (see resample for more information). To disable this, the user can pass pad_data keyword argument when loading datasets:
>>> scn.load([0.6, 10.8], pad_data=False)For geostationary products, where the imagery is stored in the files in a flipped orientation (e.g. MSG SEVIRI L1.5 data which is flipped upside-down and left-right), the keyword argument upper_right_corner can be passed into the load call to automatically flip the datasets to the wished orientation. Accepted argument values are 'NE', 'NW', 'SE', 'SW', and 'native'. By default, no flipping is applied (corresponding to upper_right_corner='native') and the data is delivered in the original format. To get the data in the common upright orientation, load the datasets using e.g.:
>>> scn.load(['VIS008'], upper_right_corner='NE')Note
If a dataset could not be loaded there is no exception raised. You must check the scn.missing_datasets <satpy.scene.Scene.missing_datasets> property for any DataID that could not be loaded.
To find out what datasets are available from a reader from the files that were provided to the Scene use ~satpy.scene.Scene.available_dataset_ids:
>>> scn.available_dataset_ids()Or ~satpy.scene.Scene.available_dataset_names for just the string names of Datasets:
>>> scn.available_dataset_names()Satpy provides a utility ~satpy.readers.find_files_and_readers for searching for files in a base directory matching various search parameters. This function discovers files based on filename patterns. It returns a dictionary mapping reader name to a list of filenames supported. This dictionary can be passed directly to the ~satpy.scene.Scene initialization.
>>> from satpy import find_files_and_readers, Scene
>>> from datetime import datetime
>>> my_files = find_files_and_readers(base_dir='/data/viirs_sdrs',
... reader='viirs_sdr',
... start_time=datetime(2017, 5, 1, 18, 1, 0),
... end_time=datetime(2017, 5, 1, 18, 30, 0))
>>> scn = Scene(filenames=my_files)See the ~satpy.readers.find_files_and_readers documentation for more information on the possible parameters.
The datasets held by a scene also provide vital metadata such as dataset name, units, observation time etc. The following attributes are standardized across all readers:
name, and other identifying metadata keys: Seedev_guide/satpy_internals.start_time: Left boundary of the time interval covered by the dataset.end_time: Right boundary of the time interval covered by the dataset.area:~pyresample.geometry.AreaDefinitionor~pyresample.geometry.SwathDefinitionif data is geolocated. Areas are used for gridded projected data and Swaths when data must be described by individual longitude/latitude coordinates. See the Coordinates section below.orbital_parameters: Dictionary of orbital parameters describing the satellite's position.For geostationary satellites it is described using the following scalar attributes:
satellite_actual_longitude/latitude/altitude: Current position of the satellite at the time of observation in geodetic coordinates (i.e. altitude is relative and normal to the surface of the ellipsoid).satellite_nominal_longitude/latitude/altitude: Center of the station keeping box (a confined area in which the satellite is actively maintained in using maneuvres). Inbetween major maneuvres, when the satellite is permanently moved, the nominal position is constant.nadir_longitude/latitude: Intersection of the instrument's Nadir with the surface of the earth. May differ from the actual satellite position, if the instrument is pointing slightly off the axis (satellite, earth-center). If available, this should be used to compute viewing angles etc. Otherwise, use the actual satellite position.projection_longitude/latitude/altitude: Projection center of the re-projected data. This should be used to compute lat/lon coordinates. Note that the projection center can differ considerably from the actual satellite position. For example MSG-1 was at times positioned at 3.4 degrees west, while the image data was re-projected to 0 degrees.- [DEPRECATED]
satellite_longitude/latitude/altitude: Current position of the satellite at the time of observation in geodetic coordinates.
Note
Longitudes and latitudes are given in degrees, altitude in meters. For use in pyorbital, the altitude has to be converted to kilometers, see for example
pyorbital.orbital.get_observer_look.For polar orbiting satellites the readers usually provide coordinates and viewing angles of the swath as ancillary datasets. Additional metadata related to the satellite position include:
tle: Two-Line Element (TLE) set used to compute the satellite's orbit
raw_metadata: Raw, unprocessed metadata from the reader.
Note that the above attributes are not necessarily available for each dataset.
Each ~xarray.DataArray produced by Satpy has several Xarray coordinate variables added to them.
xandy: Projection coordinates for gridded and projected data. By default y and x are the preferred dimensions for all 2D data, but these coordinates are only added for gridded (non-swath) data. For 1D data only theydimension may be specified.crs: A~pyproj.crs.CRSobject defined the Coordinate Reference System for the data. Requires pyproj 2.0 or later to be installed. This is stored as a scalar array by Xarray so it must be accessed by doingcrs = my_data_arr.attrs['crs'].item(). For swath data this defaults to alonglatCRS using the WGS84 datum.longitude: Array of longitude coordinates for swath data.latitude: Array of latitude coordinates for swath data.
Readers are free to define any coordinates in addition to the ones above that are automatically added. Other possible coordinates you may see:
acq_time: Instrument data acquisition time per scan or row of data.
This is described in the developer guide, see dev_guide/custom_reader.
satpy.readers.hrit_base
satpy.readers.seviri_l1b_hrit
satpy.readers.hrit_jma
satpy.readers.goes_imager_hrit
satpy.readers.electrol_hrit
satpy.readers.modis_l1b
satpy.readers.modis_l2