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We report on the first comprehensive study of the coronal mass ejections (CMEs) associated with ~25 MeV solar energetic-proton (SEP) events in 1980 – 2013 observed in the low/inner corona by the Mauna Loa Solar Observatory (MLSO) Mk3 and Mk4 coronameters. Where possible, these observations are combined with space-based observations from the Solar Maximum Mission C/P, P78-1 SOLWIND, or SOHO/LASCO coronagraphs. The aim of the study is to understand directly measured (rather than inferred from proxies) CME motions in the low to midcorona and their association with SEP acceleration, and hence attempt to identify early signatures that are characteristic of SEP acceleration in ground-based CME observations that may be used to warn of impending SEP events. Although we find that SEP events are associated with CMEs that are on average faster and wider than typical CMEs observed by MLSO, a major challenge turns out to be determining reliable estimates of the CME dynamics in the low corona from the 3-min cadence Mk3/4 observations since different analysis techniques can produce inconsistent results. This complicates the assessment of what early information on a possible SEP event is available from these low-coronal observations.

These are the memoirs of fifty years of research in solar physics, closely related to the history of three of the major solar space missions, from the Solar Maximum Mission, SMM, to Solar Orbiter, at present in navigation toward vantage points closer and closer to the Sun. My interest in solar physics was stimulated by the studies on cosmic rays at the University of Turin, and the research in this field initiated at Stanford University as a postdoctoral fellow in the team of John Wilcox with studies on the large-scale corona and its rotation. Thanks to Alan Gabriel, during my first space mission, SMM, I was involved in the operations and scientific data analysis of the Soft X-ray Polychromator. Together with Giancarlo Noci and Giuseppe Tondello, I participated in the realization of the UltraViolet Coronagraph Spectrometer, NASA/ASI, flown on-board SOHO. After this experience there was the opportunity to participate in the formulation of the proposal of the Solar Orbiter mission, and to guide the team, which for this mission developed the Metis coronagraph, up to the delivery of the instrument to the European Space Agency in 2017.

The ionospheric total electron content (TEC) is susceptible to factors, such as solar and geomagnetic activities, resulting in the enhancement of its non-stationarity and nonlinear characteristics, which aggravate the impact on radio communications. In this study, based on the NeuralProphet hybrid prediction framework, a regional ionospheric TEC prediction model (multi-factor NeuralProphet model, MF-NPM) considering multiple factors was constructed by taking solar activity index, geomagnetic activity index, geographic coordinates, and IGS GIM data as input parameters. Data from 2009 to 2013 were used to train the model to achieve forecasts of regional ionospheric TEC at different latitudes during the solar maximum phase (2014) and geomagnetic storms by sliding 1 day. In order to verify the prediction performance of the MF-NPM, the multi-factor long short-term memory neural network (LSTMNN) model was also constructed for comparative analysis. At the same time, the TEC prediction results of the two models were compared with the IGS GIM and CODE 1-day predicted GIM products (COPG_P1). The results show that the MF-NPM achieves good prediction performance effectively. The RMSE and relative accuracy (RA) of MF-NPM are 2.33 TECU and 93.75%, respectively, which are 0.77 and 1.87 TECU and 1.91% and 6.68% better than LSTMNN and COPG_P1 in the solar maximum phase (2014). During the geomagnetic storm, the RMSE and RA of TEC prediction results based on the MF-NPM are 3.12 TECU and 92.86%, respectively, which are improved by 1.25 and 2.30 TECU and 2.38% and 7.24% compared with LSTMNN and COPG_P1. Furthermore, the MF-NPM also achieves better performance in low–mid latitudes.

Since the first successful on-orbit repair mission in 1984 to the Solar Maximum Mission (SMM) satellite, considerable progress has been made in the field of On-orbit Servicing, Assembly, and Manufacturing (OSAM) of spacecraft using either human-guided or autonomous robots. This article aims to provide a review of state-of-the-art efforts in this field and the necessary technologies to achieve the ultimate objective of autonomous spacecraft repairs while in orbit. The article covers the literature relevant to OSAM, including a brief overview of OSAM, inspection technologies, manufacturing and repair technologies, state-of-the-art robotic technologies capable of performing the required tasks, and intelligent path planning of robots. The article also highlights the research’s location, timeframe, and public versus private sector efforts, and outlines future directions in this field. This article aims to foster a community of researchers and public-private partnerships working towards the common objective of autonomous robotic inspection and repair of on-orbit spacecraft.

A review of solar cycle prediction methods and their performance is given, including early forecasts for Cycle 25. The review focuses on those aspects of the solar cycle prediction problem that have a bearing on dynamo theory. The scope of the review is further restricted to the issue of predicting the amplitude (and optionally the epoch) of an upcoming solar maximum no later than right after the start of the given cycle. Prediction methods form three main groups. Precursor methods rely on the value of some measure of solar activity or magnetism at a specified time to predict the amplitude of the following solar maximum. The choice of a good precursor often implies considerable physical insight: indeed, it has become increasingly clear that the transition from purely empirical precursors to model-based methods is continuous. Model-based approaches can be further divided into two groups: predictions based on surface flux transport models and on consistent dynamo models. The implicit assumption of precursor methods is that each numbered solar cycle is a consistent unit in itself, while solar activity seems to consist of a series of much less tightly intercorrelated individual cycles. Extrapolation methods, in contrast, are based on the premise that the physical process giving rise to the sunspot number record is statistically homogeneous, i.e., the mathematical regularities underlying its variations are the same at any point of time, and therefore it lends itself to analysis and forecasting by time series methods. In their overall performance during the course of the last few solar cycles, precursor methods have clearly been superior to extrapolation methods. One method that has yielded predictions consistently in the right range during the past few solar cycles is the polar field precursor. Nevertheless, some extrapolation methods may still be worth further study. Model based forecasts are quickly coming into their own, and, despite not having a long proven record, their predictions are received with increasing confidence by the community.

We establish a catalog of interplanetary coronal mass ejections (ICMEs) during the period from 1995 to 2015 using the in-situ observations from the Wind and ACE spacecraft. Based on this catalog, we extend the statistical properties of ICMEs to the maximum phase of Solar Cycle 24. We confirm previous results that the yearly occurrence frequencies of ICMEs and shocks, the ratios of ICMEs driving shocks are correlated with the sunspot numbers. For the magnetic cloud (MC), we confirm that the yearly occurrence frequencies of MCs do not show any correlation with sunspot numbers. The highest MC ratio of ICME occurred near the solar minimum. In addition, we analyzed the yearly variation of the ICME parameters. We found that the ICME velocities, the magnetic-field strength, and their related parameters are varied in pace with solar-cycle variation. At the solar maximum, ICMEs move faster and carry a stronger magnetic field. By comparing the parameters between MCs and non-MC ejecta, we confirm the result that the magnetic-field intensities of MC are higher than those in non-MC ejecta. Furthermore, we also discuss the forward shocks driven by ICMEs. We find that one half of the ICMEs have upstream shocks and ICMEs with shocks have faster speed and higher magnetic-field strength than the ICMEs without shocks. The magnetic-field parameters and solar-wind plasma parameters in the shock sheath regions are higher than those in the ejecta regions of ICMEs from a statistical point of view.

Using the 8.5‐year Venus Express measurements, we demonstrate the asymmetric plasma distributions in the Venusian magnetosheath. An escaping plume is formed by pickup oxygen ions in the hemisphere where the motional electric field points outward from Venus, while the velocity of solar wind protons is faster in the opposite hemisphere. The pickup O+ escape rate is estimated to be (3.6 ± 1.4) × 1024 s−1 at solar maximum, which is comparable to the ion loss rate through the magnetotail, and (1.3 ± 0.4) × 1024 s−1 at solar minimum. The increase of O+ fluxes with extreme ultraviolet (EUV) intensity is significant upstream of the bow shock, partially attributed to the increase of exospheric neutral oxygen density. However, the solar wind velocity just has a slight effect on the pickup O+ escape rate in the magnetosheath, while the effect of solar wind density is not observed. Our results suggest the pickup O+ escape rate is mainly controlled by EUV radiation. Plain Language Summary The atmospheric evolution and water escape of Venus might be influenced by the solar wind‐Venus interaction. The atoms outside the induced magnetosphere are ionized by the solar radiation and accelerated to the escape velocity by solar wind electric field. In this way, the oxygen ions are picked up by solar wind and lost from the atmosphere to space. We use the data from Venus Express spacecraft to analyze the distribution of pickup oxygen ions in the vicinity of the planet. The planetary oxygen ions form a strong escaping plume, indicating the pickup process is an efficient escape channel removing the atmospheric particles. With an enhanced solar extreme ultraviolet radiation, the escape rate through this channel would be higher because more ions are produced and then picked up. This indicates an enhanced ion loss billions of years ago since the young Sun is more active, which might be a reason for the disappearance of a presumably‐existed ocean. Key Points The pickup O+ escape rate at Venus increases with solar activity, and it is comparable to the ion loss rate through the magnetotail The solar wind velocity has a slight effect on the pickup O+ escape rate in the magnetosheath The neutral oxygen density upstream of the bow shock might increase by a factor of two from solar minimum to maximum

Potential deleterious health effects to astronauts induced by space radiation is one of the most important long-term risks for human space missions, especially future planetary missions to Mars which require a return-trip duration of about 3 years with current propulsion technology. In preparation for future human exploration, the Radiation Assessment Detector (RAD) was designed to detect and analyze the most biologically hazardous energetic particle radiation on the Martian surface as part of the Mars Science Laboratory (MSL) mission. RAD has measured the deep space radiation field within the spacecraft during the cruise to Mars and the cosmic ray induced energetic particle radiation on Mars since Curiosity’s landing in August 2012. These first-ever surface radiation data have been continuously providing a unique and direct assessment of the radiation environment on Mars. We analyze the temporal variation of the Galactic Cosmic Ray (GCR) radiation and the observed Solar Energetic Particle (SEP) events measured by RAD from the launch of MSL until December 2020, i.e., from the pre-maximum of solar cycle 24 throughout its solar minimum until the initial year of Cycle 25. Over the long term, the Mars’s surface GCR radiation increased by about 50% due to the declining solar activity and the weakening heliospheric magnetic field. At different time scales in a shorter term, RAD also detected dynamic variations in the radiation field on Mars. We present and quantify the temporal changes of the radiation field which are mainly caused by: (a) heliospheric influences which include both temporary impacts by solar transients and the long-term solar cycle evolution, (b) atmospheric changes which include the Martian daily thermal tide and seasonal CO2 cycle as well as the altitude change of the rover, (c) topographical changes along the rover path-way causing addition structural shielding and finally (d) solar particle events which occur sporadically and may significantly enhance the radiation within a short time period. Quantification of the variation allows the estimation of the accumulated radiation for a return trip to the surface of Mars under various conditions. The accumulated GCR dose equivalent, via a Hohmann transfer, is about 0.65±0.24 sievert and 1.59±0.12 sievert during solar maximum and minimum periods, respectively. The shielding of the GCR radiation by heliospheric magnetic fields during solar maximum periods is rather efficient in reducing the total GCR-induced radiation for a Mars mission, by more than 50%. However, further contributions by SEPs must also be taken into account. In the future, with advanced nuclear thrusters via a fast transfer, we estimate that the total GCR dose equivalent can be reduced to about 0.2 sievert and 0.5 sievert during solar maximum and minimum periods respectively. In addition, we also examined factors which may further reduce the radiation dose in space and on Mars and discuss the many uncertainties in the interpreting the biological effect based on the current measurement.

Both coronal holes and active regions are source regions of the solar wind. The distribution of these coronal structures across both space and time is well known, but it is unclear how much each source contributes to the solar wind. In this study we use photospheric magnetic field maps observed over the past four solar cycles to estimate what fraction of magnetic open solar flux is rooted in active regions, a proxy for the fraction of all solar wind originating in active regions. We find that the fractional contribution of active regions to the solar wind varies between 30% to 80% at any one time during solar maximum and is negligible at solar minimum, showing a strong correlation with sunspot number. While active regions are typically confined to latitudes ±30 ∘ in the corona, the solar wind they produce can reach latitudes up to ±60 ∘ . Their fractional contribution to the solar wind also correlates with coronal mass ejection rate, and is highly variable, changing by ±20% on monthly timescales within individual solar maxima. We speculate that these variations could be driven by coronal mass ejections causing reconfigurations of the coronal magnetic field on sub-monthly timescales.

Space weather has long been known to approximately follow the solar cycle, with geomagnetic storms occurring more frequently at solar maximum than solar minimum. There is much debate, however, about whether the most hazardous events follow the same pattern. Extreme events – by definition – occur infrequently, and thus establishing their occurrence behaviour is difficult even with very long space-weather records. Here we use the 150-year a a H record of global geomagnetic activity with a number of probabilistic models of geomagnetic-storm occurrence to test a range of hypotheses. We find that storms of all magnitudes occur more frequently during an active phase, centred on solar maximum, than during the quiet phase around solar minimum. We also show that the available observations are consistent with the most extreme events occurring more frequently during large solar cycles than small cycles. Finally, we report on the difference in extreme-event occurrence during odd- and even-numbered solar cycles, with events clustering earlier in even cycles and later in odd cycles. Despite the relatively few events available for study, we demonstrate that this is inconsistent with random occurrence. We interpret this finding in terms of the overlying coronal magnetic field and enhanced magnetic-field strengths in the heliosphere, which act to increase the geoeffectiveness of sheath regions ahead of extreme coronal mass ejections. Putting the three “rules” together allows the probability of extreme event occurrence for Solar Cycle 25 to be estimated, if the magnitude and length of the coming cycle can be predicted. This highlights both the feasibility and importance of solar-cycle prediction for planning and scheduling of activities and systems that are affected by extreme space weather.