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 similar to 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. - Solar activity is quite correlated with sunspot numbers. Alternating periods between solar minima and minima, termed solar cycle, usually occur every similar to 11 years. As a result, researchers often attempt to predict sunspot occurrences for the following solar cycle. Solar perturbations occur more frequently during periods of high solar activity, and Earth-bound perturbations can disturb the Earth's magnetic field in geospace and on the ground, affecting satellites and power infrastructure. In this work, we use an artificial intelligence supervised model to predict the number of shock occurrences in the ongoing solar cycle (beginning December 2019) by training the model with observations of sunspots and solar perturbations in the previous two solar cycles (August 1996-December 2019). Then, sunspot number predictions for the ongoing solar cycle are applied to the model, and predictions for the solar perturbations are obtained. We find that the number of predicted solar perturbations is similar to 50% higher than their occurrence number in the previous solar cycle (December 2008-December 2019). Finally, we discuss how this relatively higher number of predicted solar perturbations can impact space weather research given the unprecedented number of data sets available in geospace and on the ground in the upcoming years. - SSN and shock count data in SC23-24 are used with SSN predictions for SC25 in a supervised regression model to estimate shock counts in SC25 We predict SC25 (275) will have similar to 48% more shocks in comparison to SC24 (187), but it will have fewer shocks in comparison to SC23 (343) SC25 will offer unprecedented opportunities for space weather research given the availability of many data sets from space to the ground