T. Barata, D. Del Moro, R. Erdelyi, J. Fernandes, R. Gafeira, M. Georgoulis, K. Murawski, S. Poedts, R. Vainio, A. Afanasiev, M. B. Korsós, A. Boiko, L. Jonh, S. Biswal, S. L. L. Bourgeois, G. Francisco, A. André-Hoffmann, E. Husidic, S. Koya, M. Kumar, R. Mugatwala, G. Nogueira, A. Wagner, E. K. J. Kilpua

Abstract

Motivation and Aims: The main objectives of this paper are twofold: (1) to present the Space Weather Awareness Training Network (SWATNet), an innovative Marie Skłodowska-Curie Training Network designed to provide high-quality doctoral training in space weather, and (2) to highlight the scientific advances achieved within the project. Methods: By combining cutting-edge research with structured international and intersectoral training, SWATNet reached fundamental advances in understanding space weather phenomena and trained a new generation of scientists equipped to tackle modern challenges in both research and industry. Results: SWATNet delivered advancements in modelling solar eruptions and the solar corona, and improved studies of the propagation and transport of Solar Energetic Particles, often utilising interdisciplinary methods. These include machine and deep learning, image processing, and various numerical modelling approaches. The research produced 26 peer-reviewed journal articles, along with various presentations at international conferences. In addition, SWATNet successfully completed its ambitious training programme on practical observatory and industry training.

Keywords
Space weather / Solar activity / Corona and heliosphere / Modelling and forecasting / Artificial intelligence and Machine learning and Deep learning

Journal of Space Weather and Space Climate
Volume 16, Number 27, Page 26
2026 August

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