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Abstract To gain deeper insights into radiation belt loss into the atmosphere, a statistical study of MeV electron precipitation during radiation belt dropout events is undertaken. During these events, electron intensities often drop by an order of magnitude or more within just a few hours. For this study, dropouts are defined as a decrease by at least a factor of five in less than 8 hours. Van Allen probe measurements are employed to identify dropouts across various parameters, complemented by precipitation data from the CALorimetric Electron Telescope instrument on the International Space Station. A temporal analysis unveils a notable increase in precipitation occurrence and intensity during dropout onset, correlating with the decline of SYM‐H, the north‐south component of the interplanetary magnetic field, and the peak of the solar wind dynamic pressure. Moreover, dropout occurrences show correlations with the solar cycle, exhibiting maxima at the spring and autumn equinoxes. This increase during equinoxes reflects the correlation between equinoxes and the SYM‐H index, which itself exhibits a correlation with precipitation during dropouts. Spatial analysis reveals that dropouts with precipitation penetrate into lower L‐star regions, mostly reaching L‐star <4, while most dropouts without precipitation don't penetrate deeper than L‐star 5. This is consistent with the larger average dimensions of dropouts associated with precipitation. During dropouts, precipitation is predominantly observed in the dusk‐midnight sector, coinciding with the most intense precipitation events. The results of this study provide insight into the contribution of precipitation to radiation belt dropouts by deciphering when and where precipitation occurred. 

Abstract Interplanetary (IP) shocks are perturbations observed in the solar wind. IP shocks correlate well with solar activity, being more numerous during times of high sunspot numbers. Earth‐bound IP shocks cause many space weather effects that are promptly observed in geospace and on the ground. Such effects can pose considerable threats to human assets in space and on the ground, including satellites in the upper atmosphere and power infrastructure. Thus, it is of great interest to the space weather community to (a) keep an accurate catalog of shocks observed near Earth, and (b) be able to forecast shock occurrence as a function of the solar cycle (SC). In this work, we use a supervised machine learning regression model to predict the number of shocks expected in SC25 using three previously published sunspot predictions for the same cycle. We predict shock counts to be around 275 ± 10, which is ∼47% higher than the shock occurrence in SC24 (187 ± 8), but still smaller than the shock occurrence in SC23 (343 ± 12). With the perspective of having more IP shocks on the horizon for SC25, we briefly discuss many opportunities in space weather research for the remainder years of SC25. The next decade or so will bring unprecedented opportunities for research and forecasting effects in the solar wind, magnetosphere, ionosphere, and on the ground. As a result, we predict SC25 will offer excellent opportunities for shock occurrences and data availability for conducting space weather research and forecasting.