Dust Aerosol Detection, Monitoring andForecasting

The training course on 'Dust Aerosol Detection, Monitoring and Forecasting' is a Pythonbased training that provides a hands-on introduction to satellite-, ground-and model-based data used for dust monitoring and forecasting.The course is organised in three main chapters: (i) observations (satellite-and ground-based), (ii) forecast models and a (iii) practical case study.It features twelve different datasets derived from satellites, groundbased measurement networks and forecast models.The course material is developed in the form of well-described and modular Jupyter notebooks.In total, the course consists of 17 notebooks; 12 data workflows and five practical exercise notebooks.The training course is available as a JupyterBook.In addition, an executable version of each notebook can be accessed via a dedicated JupyterLab training platform, which has the required programming environment and data already preinstalled.Furthermore, the training course is also available via a GitLab repository.