LTPy - Learning tool for Python on Atmospheric Composition

Learning tool for Python (LTPy) is a Python-based series of notebooks on different open satellite- and model-based data on atmospheric pollution and climate. LTPy features data from six different satellites, including the Copernicus satellites Sentinel-3 and Sentinel-5 as well as the polar orbiting meteorological satellite series Metop and five different model-based product types from the two Copernicus services on Atmosphere Monitoring (CAMS) and Emergency Management (CEMS).

The course has the aim to facilitate the uptake and use of atmospheric composition data as well as showcasing possible application areas. LTPy is based on Jupyter notebooks, which allow for a high-level of interactive learning, as code, text description and visualisation is combined in one place. The structure of the course is aligned with a typical data analysis workflow and includes notebooks on data access, data exploration, case studies and exercises. LTPy consists of more than 50 Jupyter notebooks which are available on a Gitlab repository as well as on a dedicated LTPy JupyerLab platform, where the notebooks can be executed.