Раздел: Get ready to read and handle datasets | 2nd Joint Training Course on Atmospheric Composition (2020) | EUMETSAT

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    Welcome to the Second Joint Training Course on Atmospheric Composition   

    16 - 20 November 2020

    The European Space Agency (ESA), the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), European Center for Medium-Range Weather Forecast (ECMWF) with the Copernicus Atmosphere Monitoring Service (CAMS) are organising a second joint training course on Atmospheric Composition with a focus on air quality and data interoperability.

    The school will be fully on-line with lectures, discussions and practical sessions. We aim at fully involving participants in an interactive way.

    The specific goals of the course are:

    1. Present the state-of-the-art in air quality monitoring and modelling,
    2. Provide an overview of the different observations, tools and applications,
    3. Enhance the capacity on data access and analysis of existing and new satellite data products and monitoring services,
    4. Foster participants driven personal and team projects.

    We have prepared for you a number of resources that we invite you to look at before the course starts. Here's what you can do on this page:  

Get ready to read and handle datasets

  • Get ready to read and handle datasets

    The course makes use of datasets and tools. During the school you will be introduced to them but it is a good idea to get ready before to be efficient on your mini projects. We recommend you to:

    1. Get ready with access to data. You will be introduced to these datasets, but you can also bring your own data. Below some datasets you may start from:

    It is recommended to subscribe to the datasets (where required) before the school and be able to download the products / species of your interest.

    2. Get ready with the tools to handle the data.You may still make use of your own software, but we encourage you to download and familiarize with the tools we will use in the school. 

    Practical sessions will be available on a JupyterLab instance. JupyterLab is a pre-defined environment that gives learners direct access to the data and Python packages required for following the practicals.

    We invite you to browse through the content on the JupyterLab before the course. It is a safe learning environment, where you can make changes to the code and test the same code with e.g. a different dataset.

    How to access the JupyterLab:

    Once you are logged in, you see a folder for each practical training session:

    • 1_overview_ac_satellite_data
    • 2_harp_toolbox_gridding_exercise
    • 3_overview_cams_data
    • 4 _harp_toolbox_comparison_exercise

    NOTE: if you log into the JupyterLab, a docker image will be created. To have a clean environment for the training course, we will delete all docker images before the course starts.

    In addition you can install all materials on your computer:

    Make your local installation of python 

    To reproduce the course modules on your local setup, the following Python version and Python packages will be required:

    ESA Atmospheric Toolbox for data reading, visualization and handling

    • To install the Atmospheric Toolbox components, first install Anaconda or Miniconda for Python3, and then run the following command within your conda environment:
      conda install -c stcorp coda harp