High rate SEVIRI Level 1.5 Image Data MSG - Data Access

Prerequisites:

To search and access DEDL data a DestinE user account is needed

References:

DestinE Data Lake (DEDL) Harmonized Data Access (HDA) documentation

High Rate SEVIRI Level 1.5 Image Data - MSG - 0 degree

Credit:
This notebook uses Satpy
© 2014–2025 PyTroll community
Licensed under PyGNU GPL v3

This notebook demonstrates how to search and access MSG data using HDA and how to read, process and visualize it using satpy

The Spinning Enhanced Visible and InfraRed Imager (SEVIRI) is MSG’s primary instrument and has the capacity to observe the Earth in 12 spectral channels.

Throughout this notebook, you will learn:

Authenticate: How to authenticate for searching and access DEDL collections.
Search: How to search DEDL data using datetime and bbox filters.
Download: How to download DEDL data through HDA.
Read and visualize MSG data: How to load process and visualize MSG data using Satpy.

Authenticate¶

import destinelab as deauth

import requests
import json
import os
import zipfile
import datetime
import shutil
from getpass import getpass

DESP_USERNAME = input("Please input your DESP username or email: ")
DESP_PASSWORD = getpass("Please input your DESP password: ")

auth = deauth.AuthHandler(DESP_USERNAME, DESP_PASSWORD)
access_token = auth.get_token()
if access_token is not None:
    print("DEDL/DESP Access Token Obtained Successfully")
else:
    print("Failed to Obtain DEDL/DESP Access Token")

auth_headers = {"Authorization": f"Bearer {access_token}"}

Search¶

HDA endpoint¶

HDA API is based on the Spatio Temporal Asset Catalog specification (STAC), it is convenient define a costant with its endpoint.

HDA_STAC_ENDPOINT="https://hda.data.destination-earth.eu/stac/v2"

COLLECTION_ID = "EO.EUM.DAT.MSG.HRSEVIRI"

response = requests.post(HDA_STAC_ENDPOINT+"/search", headers=auth_headers, json={
    "collections": [COLLECTION_ID],
    "datetime": "2023-08-06T08:00:00Z/2023-08-07T00:00:00Z"
})

from IPython.display import JSON

product = response.json()["features"][0]
JSON(product)

Download¶

from tqdm import tqdm
import time

# Define a list of assets to download
#assets = ["Oa08_radiance.nc", "Oa06_radiance.nc", "Oa02_radiance.nc"]
assets = ["downloadLink"]

for asset in assets:
    download_url = product["assets"][asset]["href"]
    print(download_url)
    filename = asset
    print(filename)
    response = requests.get(download_url, headers=auth_headers)
    total_size = int(response.headers.get("content-length", 0))

    print(f"downloading {filename}")

    with tqdm(total=total_size, unit="B", unit_scale=True) as progress_bar:
        with open(filename, 'wb') as f:
            for data in response.iter_content(1024):
                progress_bar.update(len(data))
                f.write(data)

zf=zipfile.ZipFile(filename)
with zipfile.ZipFile(filename, 'r') as zip_ref:
    zip_ref.extractall('.')

Satpy¶

The Python package satpy supports reading and loading data from many input files. For MSG data and the Native format, we can use the satpy reader 'seviri_l1b_native.

pip install --quiet satpy

Import required libraries

from satpy.scene import Scene
from satpy.composites import GenericCompositor
from satpy.writers import to_image
from satpy.resample import get_area_def
from satpy import available_readers

import warnings
warnings.filterwarnings('ignore')
warnings.simplefilter(action = "ignore", category = RuntimeWarning)

file='MSG3-SEVI-MSG15-0100-NA-20230806081241.839000000Z-NA.nat'

Read and load data¶

We use the Scene constructor from the satpy library, a Scene object represents a single geographic region of data. Once loaded we can list all the available bands (spectral channel) for that scene.

# read the file
scn = Scene(reader='seviri_l1b_native', filenames=[file])
# print available datasets
scn.available_dataset_names()

With the function load(), you can specify an individual band by name. If you then select the loaded band, you see the xarray.DataArray band object

# load bands 
scn.load(['HRV','IR_108'])
scn['IR_108']

scn['IR_108'].attrs.keys()

scn['IR_108'].attrs['wavelength']

Visualize data combining bands¶

The Satpy function available_composite_ids() returns a list of available composite IDs.

scn = Scene(reader="seviri_l1b_native", 
             filenames=[file])

scn.available_composite_ids()

composite_id = ["natural_color"]
scn.load(composite_id, upper_right_corner="NE")

scn_cropped = scn.crop(ll_bbox=(-5, 31, 20, 51))
scn_cropped.show("natural_color")


composite_id = ["colorized_ir_clouds"]
scn.load(composite_id, upper_right_corner="NE")

scn_cropped = scn.crop(ll_bbox=(-5, 31, 20, 51))
scn_cropped.show("colorized_ir_clouds")