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The Empirical model for Solar Proton Events Real Time Alert (ESPERTA) exploits three solar parameters (flare longitude, soft X-ray fluence, and radio fluence) to provide a timely prediction for the occurrence of solar proton events (SPEs, i.e., when the >10MeV proton flux is ≥10 pfu) after the emission of a ≥M2 flare. In addition, it makes a prediction for the most dangerous SPEs for which the >10 MeV proton flux is ≥100 pfu. In this paper, we study two different ways to upgrade the ESPERTA model and implement it in real time: 1) by using ground based observations from the LOFAR stations; 2) by applying a novel machine learning algorithm to flare-based parameters to provide early warnings of SPE occurrence together with a fine-tuned radiation storm level. As a last step, we perform a preliminary study using a neural network to forecast the proton flux 1-hour ahead to complement the ESPERTA tool. We evaluate the models over flare and SPE data covering the last two solar cycles and discuss their performance, limits, and advantages.

The present study investigated whether increasing morning rectal temperatures (Trec) to evening levels, or increasing morning and evening Trec to an “optimal” level (38.5°C), resulting in increased muscle temperatures (Tm), would offset diurnal variation in repeated sprint (RS) performance in a causal manner. Twelve trained males underwent five sessions [age (mean ± SD) 21.0 ± 2.3 years, maximal oxygen consumption (V̇O2max) 60.0 ± 4.4 mL.kg-1 min-1, height 1.79 ± 0.06 m, body mass 78.2 ± 11.8 kg]. These included control morning (M, 07:30 h) and evening (E, 17:30 h) sessions (5-min warm-up), and three further sessions consisting of a warm-up morning trial (ME, in 39-40°C water) until Trec reached evening levels; two “optimal” trials in the morning and evening (M38.5 and E38.5, in 39-40°C water) respectively, until Trec reached 38.5°C. All sessions included 3 × 3-s task-specific warm-up sprints, thereafter 10 × 3-s RS with 30-s recoveries were performed a non-motorised treadmill. Trec and Tm measurements were taken at the start of the protocol and following the warm-up periods. Values for Trec and Tm at rest were higher in the evening compared to morning values (0.48°C and 0.69°C, p < 0.0005). RS performance was lower (7.8-8.3%) in the M for distance covered (DC; p = 0.002), average power (AP; p = 0.029) and average velocity (AV; p = 0.002). Increasing Trec in the morning to evening values or optimal values (38.5°C) did not increase RS performance to evening levels (p = 1.000). However, increasing Trec in the evening to “optimal” level through a passive warm-up significantly reduced DC (p = 0.008), AP (p < 0.0005) and AV (p = 0.007) to values found in the M condition (6.0-6.9%). Diurnal variation in Trec and Tm is not wholly accountable for time-of-day oscillations in RS performance on a non-motorised treadmill; the exact mechanism(s) for a causal link between central temperature and human performance are still unclear and require more research. [ABSTRACT FROM AUTHOR]