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Register a new userSolar Cycle Dependence of ICME Composition
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Coronal mass ejections (CMEs) are one of the most energetic explosions in the solar atmosphere, and their occurrence rates exhibit obvious solar cycle dependence with more events taking place around solar maximum. Composition of interplanetary CMEs (ICMEs), referring to the charge states and elemental abundances of ions, opens an important avenue to investigate CMEs. In this paper, we conduct a statistical study on the charge states of five elements (Mg, Fe, Si, C, and O) and the relative abundances of six elements (Mg/O, Fe/O, Si/O, C/O, Ne/O, and He/O) within ICMEs from 1998 to 2011, and find that all the ICME compositions possess the solar cycle dependence. All of the ionic charge states and most of the relative elemental abundances are positively correlated with sunspot numbers (SSNs), and only the C/O ratios are inversely correlated with the SSNs. The compositions (except the C/O) increase with the SSNs during the ascending phase (1998--2000 and 2009--2011) and remain elevated during solar maximum and descending phase (2000--2005) compared to solar minimum (2007--2009). The charge states of low-FIP (first ionization potential) elements (Mg, Fe, and Si) and their relative abundances are correlated well, while no clear correlation is observed between the C$^{6+}$/C$^{5+}$ or C$^{6+}$/C$^{4+}$ and C/O. Most interestingly, we find that the Ne/O ratios of ICMEs and slow solar wind have the opposite solar cycle dependence.
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A review of solar cycle prediction methods and their performance is given, including forecasts for cycle 24 and focusing on 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. Their implicit assumption 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. Finally, instead of an analysis of observational data alone, model based predictions use physically (more or less) consistent dynamo models in their attempts to predict solar activity. In their overall performance precursor methods have clearly been superior to extrapolation methods. Nevertheless, some extrapolation methods may still be worth further study. Model based forecasts have not yet have had a chance to prove their skills. One method that has yielded predictions consistently in the right range during the past few solar cycles is that of K. Schatten et al., whose approach is mainly based on the polar field precursor. The incipient cycle 24 will probably mark the end of the Modern Maximum, with the Sun switching to a state of less strong activity.
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. 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.
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