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The need for real-time monitoring and alerting systems for space weather hazards has grown significantly in the last two decades. One of the most important challenges for space mission operations and planning is the prediction of solar proton events (SPEs). In this context, artificial intelligence and machine learning techniques have opened a new frontier, providing a new paradigm for statistical forecasting algorithms. The great majority of these models aim to predict the occurrence of an SPE, i.e., they are based on the classification approach. This work is oriented toward the successful implementation of onboard prediction systems, which is essential for the future of space exploration. We present a simple and efficient machine learning regression algorithm that is able to forecast the energetic proton flux up to 1 hr ahead by exploiting features derived from the electron flux only. This approach could be helpful in improving monitoring systems of the radiation risk in both deep space and near-Earth environments. The model is very relevant for mission operations and planning, especially when flare characteristics and source location are not available in real time, as at Mars distance. [ABSTRACT FROM AUTHOR]

Interplanetary coronal mass ejections (ICMEs), generally containing magnetic clouds (MCs), are associated with galactic-cosmic ray (GCR) intensity depressions known as Forbush decreases (FDs). An ICME was observed at L1 between 2016 August 2 at 14:00 UT and August 3 at 03:00 UT. The MC region was identified and its magnetic configuration was retrieved by using the Grad–Shafranov (GS) reconstruction. A weak FD in the GCR count-rate was observed on 2016 August 2 by a particle detector on board the European Space Agency LISA Pathfinder mission. The spacecraft orbited around L1 and the particle detector allowed us to monitor the GCR intensity at energies above 70 MeV n−1. A 9% decrease in the cosmic-ray intensity was observed during the ICME passage. The first structure of the ICME caused a 6.4% sharp decrease, while the MC produced a 2.6% decrease. A suited full-orbit test-particle simulation was performed on the MC configuration obtained through the GS reconstruction. The FD amplitude and time profile obtained through the simulation show an excellent agreement with observations. The test-particle simulation allows us to derive the energy dependence of the MC-driven FD providing an estimate of the amplitude at different rigidities, here compared with several neutron monitor observations. This work points out the importance of the large-scale MC configuration in the interaction between GCRs and ICMEs and suggests that particle drifts have a primary role in modulating the GCR intensity within the MC under study and possibly in at least all slowly expanding ICMEs lacking a shock/sheath region. [ABSTRACT FROM AUTHOR]