MTG FCI - Natural Color Example

Satpy includes a reader for the Meteosat Third Generation (MTG) FCI Level 1c data. The following Python code snippet shows an example on how to use Satpy to generate a Natural Color RGB composite over the European area.


This example is currently a work in progress. Some of the below code may not work with the currently released version of Satpy. Additional updates to this example will be coming soon.


For reading compressed data, a decompression library is needed. Either install the FCIDECOMP library (see the FCI L1 Product User Guide, or the hdf5plugin package with:

pip install hdf5plugin


conda install hdf5plugin -c conda-forge

If you use hdf5plugin, make sure to add the line import hdf5plugin at the top of your script.

from satpy.scene import Scene
from satpy import find_files_and_readers

# define path to FCI test data folder
path_to_data = 'your/path/to/FCI/data/folder/'

# find files and assign the FCI reader
files = find_files_and_readers(base_dir=path_to_data, reader='fci_l1c_nc')

# create an FCI scene from the selected files
scn = Scene(filenames=files)

# print available dataset names for this scene (e.g. 'vis_04', 'vis_05','ir_38',...)

# print available composite names for this scene (e.g. 'natural_color', 'airmass', 'convection',...)

# load the datasets/composites of interest
scn.load(['natural_color','vis_04'], upper_right_corner='NE')
# note: the data inside the FCI files is stored upside down. The upper_right_corner='NE' argument
# flips it automatically in upright position.

# you can access the values of a dataset as a Numpy array with
vis_04_values = scn['vis_04'].values

# resample the scene to a specified area (e.g. "eurol1" for Europe in 1km resolution)
scn_resampled = scn.resample("eurol", resampler='nearest', radius_of_influence=5000)

# save the resampled dataset/composite to disk
scn_resampled.save_dataset("natural_color", filename='./fci_natural_color_resampled.png')