Joint Training School and Workshop on Dust Aerosol Detection and Monitoring
Topic outline
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This online school is jointly organized by EUMETSAT, the WMO SDS-WAS Regional Center (which is managed by the Barcelona Supercomputing Center, BSC, and the Spanish Meteorological State Agency, AEMET) and ACTRIS with the support of the Copernicus programme.Learning objectives
The training aims to enable participants to be aware of satellite-based, ground-based and model-based products. Participants will also learn more about the applicability and fitness-for-purpose of the respective products.
Target audience
The training school aims to build capacity and improve skills in aerosol detection and monitoring for users from research and academia, and meteorological and transnational agencies, with a regional focus on Europe, North Africa, Middle East and Sahelian Africa. However, attendance is open to all countries.
On this course page you can find preparatory material on Python and how to access data. We will have an optional clinic session to go over your questions on 16th February 2023 at 13:00 CET.
During the school, we will have lectures from scientific experts and hands-on problem-based practicals.
All activities will be in English.
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Lecturers and speakers
- Melanie Ades and Angela Benedetti, ECMWF CAMS
- Sara Basart, WMO/WMO SDS-WAS
- Federico Fierli, EUMETSAT
- Lucia Mona, CNR-IMAA
- Xavier Querol and Andrés Alastuey, CSIC-IDAEA
- Anu-Maija Sundström, Finnish Meteorological Institute
- Sabrina Szeto, EUMETSAT
- Sophie Vandenbussche, Royal Belgian Institute for Space Aeronomy
- Julia Wagemann, EUMETSAT
- Ernest Werner, AEMET
Communications tools
We will be using Slido in support of Q&As during lectures and slack to discuss and exchange with all selected participants during the School. Access codes will be share with participants via email. -
Questionnaire
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Each week, we will release a set of notebooks for you to go through ahead of the Joint Dust Training School. This material is optional, but it will be very helpful for those who may be new to programming or for those who are new to the data types we will be using.
We will answer any questions during the optional clinic on 16th February 2023 at 13:00 (CET). Selected participants will receive the Zoom link. The clinic agenda is below:
13:00 - 14:00: Python 101
14:00 - 15:00: Intro to Jupyter
15:00 - 16:00: Data Access & Workflows
Practical materials
- Python - Preparatory Material (link opens in a new tab)
This notebook will introduce you to the Python programming language and useful Python libraries for processing and visualising data that we will use during this training school.
- Introduction to Project Jupyter (link opens in a new tab)
Project Jupyter offers different tools to facilitate interactive computing, either with a web-based application (Jupyter Notebooks), an interactive development environment (JupyterLab) or via a JupyterHub that brings interactive computing to groups of us.
- JupyterLab (link opens in a new tab)
JupyterLab is a web-based interactive development environment for Jupyter notebooks, code, and data. This notebook will introduce you to a JupyterLab training platform that will be used in this training.
- Jupyter Notebook (link opens in a new tab)
The Jupyter Notebook is a web-based application that records your data processing workflow from describing the steps, executing your code and visualising the results. It is similar to a writing a recipe or lab notebook. This notebook will introduce you to what Jupyter Notebooks can do and how you can use them effectively. - Data access (link opens in a new tab)
This notebook will introduce you to the data sources that we will be working on during this training school. - Troubleshooting (link opens in a new tab)
This notebook gives some hints about what you can do if your notebook or a code cell does not react as expected, or you think something isn't working in your Jupyter Notebook.
Replicating the JupyterLab environment locally (link opens in a new tab)
This notebook will provide guidance on how to replicate the JupyterLab environment we used during the training school on your local machine (your laptop or desktop).
Data Workflows for Model Data - Python - Preparatory Material (link opens in a new tab)