A2 Refereed review article in a scientific journal
Predicting Solar Energetic Particles: Solar Storm Watch - Preparing for Space Odyssey
Authors: Papaioannou, Athanasios; Strauss, Roelf Du Toit; Lario, David; Vainio, Rami; Wijsen, Nicolas; Afanasiev, Alexander; Anastasiadis, Anastasios; Kouloumvakos, Athanasios
Publisher: SPRINGER
Publication year: 2025
Journal: Space Science Reviews
Article number: 82
Volume: 221
Issue: 6
ISSN: 0038-6308
eISSN: 1572-9672
DOI: https://doi.org/10.1007/s11214-025-01211-4
Publication's open availability at the time of reporting: Open Access
Publication channel's open availability : Partially Open Access publication channel
Web address : https://doi.org/10.1007/s11214-025-01211-4
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/500227196
Space Weather effects produced by Solar Energetic Particles (SEPs) present a direct radiation hazard to crew and spacecraft equipment, first in interplanetary space, and then, due to secondary effects, within the Earth's magnetosphere and atmosphere. Being able to predict and/or forecast SEP events is of particular importance for the near-future planned manned missions to the Moon and Mars, as well as for our unimpeded daily living. In this review, we present key findings that have been utilized and/or explored by the scientific community over the last few decades to establish prediction schemes of SEP events. We first discuss empirical models where parameters related to the parent solar events (i.e. solar flares and coronal mass ejections) can be used to estimate both the probability of occurrence and critical properties (i.e. peak proton flux and/or fluence) of SEP events in the near-Earth environment and beyond. Next, we review physics-based modeling efforts of SEP events that are geared towards operational prediction, particularly focusing on SEP transport effects and multi-spacecraft observations. We furthermore explore the applicability of higher order multivariate, machine learning, and artificial intelligence methods and highlight the particular value and limitations of such advances. Finally, the most current operational approaches in the prediction of SEP events, together with future challenges that need to be addressed by the scientific community, are presented and discussed.
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Funding information in the publication:
Open access funding provided by HEAL-Link Greece.
