From September 2nd to 6th, 2024, I had the pleasure of attending the inaugural International Summer School on Satellite Meteorology, held at the stunning Villa Doria d’Angri in Naples. The venue offered breathtaking views of the Vesuvius volcano and the Bay of Naples, making it a truly unforgettable experience.
The summer school brought together students from around the world, primarily from Italy and Europe, but also a few from overseas. The program covered key topics such as radiative transfer theory, satellite remote sensing for clouds and precipitation, image interpretation, retrieval methods, and the use of satellite data for severe weather forecasting. We also gained insights into new satellite missions and explored how to access and utilize the wealth of satellite data available for weather and climate applications. Practical sessions included hands-on work with a radiative transfer model, lightning data analysis, and image processing, culminating in presentations of the projects we developed during the labs.
Participating in this program was especially valuable for me, as my current research focuses on satellite image analysis. The school’s content aligned perfectly with my research goals, enhancing my knowledge and providing new techniques to process and interpret satellite imagery. This is particularly relevant as I am using satellite data to train a machine learning model for classifying cloud regimes, especially in the context of heavy rainfall events.
I would like to thank the organizers for such a well-structured and engaging program, as well as for the wonderful venue, great weather, and delicious food. It was also a fantastic opportunity to meet fellow PhD students working in meteorology, which I hope will expand my professional network and foster new friendships.
Finally, I want to express my gratitude to the GSGS for their financial support, which allowed me to attend this invaluable summer school, providing a significant boost to my future academic and research prospects.

Daniele Corradini
PhD student
Institute of Geophysics and Meteorology
PhD Project: Self-supervised learning using satellite imagery for evaluating cloud structures in ICON-GLORI