Online training & Jupyter Notebooks

  • During Fall 2022, OSI SAF participated to an EUMETSAT online training course to support the development of Marine Applications. Contributing to this online course offered the occasion to develop Jupyter notebooks to support training modules for accessing, exploring and visualizing OSI SAF Sea Surface Temperature, Sea Ice, and Sea Surface Winds products.

    These notebooks are now freely available from the EUMETSAT GitLab. You'll find out in this story what the course was about and how you can access the notebooks.

  • EUMETSAT training "Supporting Marine Applications"

    OSI SAF contributed to the EUMETSAT Supporting Marine Earth Observation Applications (SMA) training course. Conducted in partnership with the Oceanography & Earth Observation Group of the National and Kapodistrian University of Athens the course supported data streams from EUMETSATs Copernicus marine missions (Sentinel-3; Sentinel-6) and those from the EUMETSAT OSI SAF.

    The course shared knowledge, skills, resources and code so attendees can independently access and process data from the EUMETSAT product catalogue for their marine work-flows and applications.

  • 2022 EUMETSAT Support Marine Earth Observation Applications (SMA) course 2022 EUMETSAT Support Marine Earth Observation Applications (SMA) course

    Training took place entirely online and through two phases.

    • Firstly, a 3-week self-paced phase involve self-paced flexible learning through webinars, forums, technical checks, documentation and assignments.
    • Secondly, a virtual classroom phase held during the final week (21 - 25 November) hosted over the tool This classroom phase included interactive tutorials, live demos, group work, and 1:1 meetings. During this intensive week, participants focused on co-creating a mini-project directly relevant their application of interest.


  • EUMETSAT training activities

    The EUMETSAT training activities support users in the member states and among the World Meteorological Organization (WMO) members in the application of EUMETSAT data, products, and services, including Copernicus data provided by EUMETSAT. Find out more on

  • Concerning OSI SAF the course was the occasion to present the Satellite Application Facility and introduce Sea Surface Temperature, Sea Ice Parameters and Wind products.

    For each product the course presents :

    • Principles of measuring a parameter
    • Product overview
    • OSI SAF portfolio
    • Product description
    • Documentation

    There were 40 participants to the course, and 3 applications particularly used OSI SAF data.

  • OSI SAF Jupyter notebooks

    Finding and accessing scientific data is the first part of any workflow, and with a good understanding of data access you can find and obtain data for a range of applications, and scale those applications from single images to whole mission archives. Therefore, different modules have been developed to showcase how to access the OSI SAF satellite data.

    Development of OSI SAF learning ressource has been achieved in the form of Jupyter notebooks for each data type :

    • Sea Ice Parameters
    • Sea Surface Temperature
    • Sea Surface Winds 

    Jupyter notebooks combine code cells with text markdown to create code that can be well documented and executable. Displayed in an interactive way using Jupyter Notebooks to get experience with executing Python code in a self-contained environment.

    Following the structure of EUMETSAT ressources, the OSI SAF learning modules are hosted on git repositories containing the following elements :

    • Conda environment file - to set up the software environment
    • Notice - to to explain the contents of the module
    • Jupyter Notebooks - detailed per product and thematic

    All OSI SAF Jupyter notebooks and learning ressources are hosted on EUMETLab. The EUMETSAT GitLab project contains groups of code repositories that have been made open to the public by EUMETSAT and collaborators. The learning modules are based on free software, open standards, and web services for interactive computing.

    • Jupyter Notebboks

      Project Jupyter provides a variety of tools to support writing and execution of scripts in an interactive environment. The Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations, narrative text, visualizations, and more. Notebooks can be executed in a local Python environment, or in a hosted Jupyter environment such as a JupyterHub or Lab.

    • GitLab logo

      GitLab is an open source end-to-end software development platform with built-in version control, issue tracking, code review, CI/CD, and more.

    • Anaconda logo

      Conda is an open-source package and environment management system that runs on Windows, macOS, and Linux. Conda quickly installs, runs, and updates packages and their dependencies. It also easily creates, saves, loads, and switches between environments on your local computer.

    • OSI SAF Notebooks OSI SAF Notebooks
  • OSI SAF Wind Notebook OSI SAF Wind Notebook

    Each module consists of a collection of python-based Jupyter-notebooks design to help users begin to work with the different products within the OSI SAF catalogue. The 3 accesible OSI SAF modules are :

    On the left you can see an example of visualization of OSI SAF Wind vectors.

  • OSI SAF SST Notebook OSI SAF SST Notebook

    Each learning module contains individual notebooks about he following topics :

    • Accessing data
    • Exploring the file structure
    • Plotting data on a map
    • Application examples

    On the right you can see an example of OSI SAF Metop-B SST global SST product.

  • Developing interactive training tools

    Developing Jupyter Notebooks to support training modules for accessing, exploring and visualizing OSI SAF Sea Surface Temperature, Sea Ice, and Sea Surface Winds product is a first step of code sharing. These notebooks are now freely available from the EUMETSAT GitLab.

    This module will be supplemented by later developments that will give hands on examples for advanced data access and applications using Python tools.

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