Review of Solar Energetic Particle Prediction Models - Kathryn Whitman; Ricky Egeland; Ian G. Richardson; Clayton Allison; Philip Quinn; Janet Barzilla; Irina Kitiashvili; Viacheslav Sadykov; Hazel M. Bain; Mark Dierckxsens; M. Leila Mays; Tilaye Tadesse; et al. (Advances in Space Research, 2023)

Dynamical information flow within the magnetosphere-ionosphere system during magnetic storms - Mirko Stumpo; Simone Benella; Giuseppe Consolini; Tommaso Alberti (Rendiconti Lincei. Scienze Fisiche e Naturali, 2023)
The direct role of successive intense magnetospheric substorms in injecting/energizing particles into the storm-time ring current is still debated and controversial. Whereas in the recent past it has been observed the absence of a net information flow between magnetic storms and substorms, previous in-situ satellite observations have evidenced that ionospheric-origin ions dominate the population of the ring current during the main phase of geomagnetic storms. As a matter of fact, the controversy arises mainly by the use of sophisticated data-driven techniques somewhat contradicting in-situ measurements. In this framework, the main aim of this work is to attempt an adaption of the powerful information-theoretic approach, i.e., the transfer entropy, in a consistent way with physics modeling and observations and to explore the possible motivations behind the underlying contradictions that emerge when these techniques are used. Our idea is to characterize the dynamics of the information flow within the magnetosphere-ionosphere system using a database of geomagnetic storms instead of considering a long time series of geomagnetic indices. We found a net information flow between the external driver and the geomagnetic indices and also between high and low latitude indices themselves, which turns out to be very well localized during the different phases of a magnetic storm.

Kramers–Moyal analysis of interplanetary magnetic field fluctuations at sub-ion scales - Simone Benella; Mirko Stumpo; Giuseppe Consolini; Tommaso Alberti; Monica Laurenza; Emiliya Yordanova (Rendiconti Lincei. Scienze Fisiche e Naturali, 2022)
In the framework of statistical time series analysis of complex dynamics, we present a multiscale characterization of solar wind turbulence in the near-earth environment. The data analysis, based on the Markov process theory, is meant to estimate the Kramers–Moyal coefficients associated with the measured magnetic field fluctuations. In fact, when the scale-to-scale dynamics can be successfully described as a Markov process, first- and second-order Kramers–Moyal coefficients provide a complete description of the dynamics in terms of Langevin stochastic process. The analysis is carried out using high-resolution magnetic field measurements gathered by Cluster during a fast solar wind period on January 20, 2007. This analysis extends recent findings in the near-Sun environment with the aim of testing the universality of the Markovian nature of the magnetic field fluctuations in the sub-ion/kinetic domain.