Preliminary prediction of solar cycles 24 and 25 based on the correlation between cycle parameters

The correlation between various parameters of solar cycles 1–23 is investigated. The derived regressions are used to make predictions of solar cycles 24 and 25. It is expected that solar cycle 24 will reach its maximum amplitude of 110.2 ± 33.4 in April–June 2012 and the next minimum will occur in December 2018–January 2019. The duration of solar cycle 24 will be about 11.1 years. Solar cycle 25 will reach its maximum amplitude of 112.3 ± 33.4 approximately in April–June 2023.     

Prediction verification of solar cycles 18–24 and a preliminary prediction of the maximum amplitude of solar cycle 25 based on the Precursor Method

Predictions of the strength of solar cycles are important and are necessary for planning long-term missions.A new solar cycle 25 is coming soon,and the amplitude is needed for space weather operators.Some predictions have been made using different methods and the values are drastically different.However,since 2015 July 1,the original sunspot number data have been entirely replaced by the Version 2.0 data series,and the sunspot number values have changed greatly.In this paper,using Version 2 smoothed sunspot numbers and aa indices,we verify the predictions for cycles 18–24 based on Ohl’s Precursor Method.Then a similar-cycles method is used to evaluate the aa minimum of 9.7(±1.1)near the start of cycle 25 and based on the linear regression relationship between sunspot maxima and aa minima,our predicted Version 2maximum sunspot number for cycle 25 is 121.5(±32.9).     

A comparative study of geomagnetic storms for solar cycles 23 and 24

The aim of this paper is to investigate the association of the geomagnetic storms with the magnitude of interplanetary magnetic field IMF (B), solar wind speed (V), product of IMF and wind speed (\(V \cdot B)\), Ap index and solar wind plasma density (\(n_{\mathrm{p}})\) for solar cycles 23 and 24. A Chree analysis by the superposed epoch method has been done for the study. The results of the present analysis showed that \(V \cdot B\) is more geoeffective when compared to V or B alone. Further the high and equal anti-correlation coefficient is found between Dst and Ap index (? 0.7) for both the solar cycles. We have also discussed the relationship between solar wind plasma density (\(n_{\mathrm{p}})\) and Dst and found that both these parameters are weakly correlated with each other. We have found that the occurrence of geomagnetic storms happens on the same day when IMF, V, Ap and \(V \cdot B\) reach their maximum value while 1 day time lag is noticed in case of solar wind plasma density with few exceptions. The study of geomagnetic storms with various solar-interplanetary parameters is useful for the study of space weather phenomenon.     

Neural network prediction of solar cycle 24

The ability to predict the future behavior of solar activity has become extremely import due to its effect on the environment near the Earth.Predictions of both the amplitude and timing of the next solar cycle will assist in estimating the various consequences of space weather.The level of solar activity is usually expressed by international sunspot number (Rz).Several prediction techniques have been applied and have achieved varying degrees of success in the domain of solar activity prediction.We predict a...     

Temporal variation of solar flare index during solar cycles 21–24

The present investigation attempts to quantify the temporal variation of Solar Flare Index(SFI)with other activity indices during solar cycles 21-24 by using different techniques such as linear regression,correlation,cross-correlation with phase lag-lead,etc.Different Solar Activity Indices(SAI)considered in this present study are Sunspot Number(SSN),10.7 cm Solar Radio Flux(F10.7),Coronal Index(CI)and MgⅡCore-to-Wing Ratio(MgⅡ).The maximum cycle amplitude of SFI and considered SAI has a decreasing trend from solar cycle 22,and cycle 24 is the weakest solar cycle among all other cycles.The SFI with SSN,F10.7,CI and MgⅡshows hysteresis during all cycles except for solar cycle 22 where both paths for ascending and descending phases are intercepting each other,thereby representing a phase reversal.A positive hysteresis circulation exists between SFI and considered SAI during solar cycles 22 and 23,whereas a negative circulation exists in cycles 21 and 24.SFI has a high positive correlation with coefficient values of 0.92,0.94,0.84 and 0.81 for SSN,F10.7,CI and MgⅡrespectively.According to crosscorrelation analysis,SFI has a phase lag with considered SAI during an odd-number solar cycle(solar cycles21 and 23)but no phase lag/lead during an even-numbered solar cycle(solar cycles 22 and 24).However,the entire smoothed monthly average SFI data indicate an in-phase relationship with SSN,F10.7 and MgⅡ,and a one-month phase lag with CI.The presence of those above characteristics strongly confirms the outcomes of different research work with various solar indices and the highest correlation exists between SFI and SSN as well as F10.7 which establishes that SFI may be considered as one of the prime activity indices to interpret the characteristics of the Sun’s active region as well as for more accurate short-range or long-range forecasting of solar events.     

Association of CMEs with solar surface activity during the rise and maximum phases of solar cycles 23 and 24

The cyclical behaviors of sunspots,flares and coronal mass ejections(CMEs) for 54 months from 2008 November to 2013 April after the onset of Solar Cycle(SC) 24 are compared,for the first time,with those of SC 23 from 1996 November to 2001 April.The results are summarized below.(i) During the maximum phase,the number of sunspots in SC 24 is significantly smaller than that for SC 23 and the number of flares in SC 24 is comparable to that of SC 23.(ii) The number of CMEs in SC 24 is larger than that in SC 23 and the speed of CMEs in SC 24 is smaller than that of SC 23 during the maximum phase.We individually survey all the CMEs(1647 CMEs) from 2010 June to 2011 June.A total of 161 CMEs associated with solar surface activity events can be identified.About 45%of CMEs are associated with quiescent prominence eruptions,27%of CMEs only with solar flares,19%of CMEs with both active-region prominence eruptions and solar flares,and 9%of CMEs only with active-region prominence eruptions.Comparing the association of the CMEs and their source regions in SC 24 with that in SC 23,we notice that the characteristics of source regions for CMEs during SC 24 may be different from those of SC 23.     

Some notes concerning the prediction of the amplitude of the solar activity cycles

The parameter G, which is determined from the general number of sunspots groups N _g according to the daily observations G=∑(1/N _g )², is offered. This parameter is calculated for the days when there is at least one sunspots group. It characterizes the minimum epoch solar activity. Parameter G mounts to the maximum during the epoch close to the minimal activity of sunspots. According to the data of the sequence of sunspots group in Greenwich–USAF/NOAA observatory format, observation data of Kislovodsk solar station and also daily Wolf number, the changes of parameter G during 100 years were reconstructed. It is demonstrated in the paper that parameter G’s amplitude in minimal solar activity n is linked with the sunspot cycle’s amplitude W _n+1 or one and half cycles. The 24th activity cycle prediction is calculated, which makes W ₂₄=135(±12).     

Polar coronal holes and solar cycles

The relationship between the geomagnetic activity of the three years preceding a sunspot minimum and the peak of the next sunspot maximum confirms the polar origin of the solar wind during one part of the solar cycle. Pointing out that the polar holes have a very small size or disappear at the time of the polar field reversal, we suggest a low latitude origin of the solar wind at sunspot maximum and we describe the cycle variation of solar wind and geomagnetic activity. In addition we note a close relationship between the maximum level of the geomagnetic activity reached few years before a solar minimum and its level at the next sunspot maximum. Studying separately the effects of both the low latitude holes and the solar activity, we point out the possibility of predicting both the level of geomagnetic activity and the sunspot number at the next sunspot maximum. As a conclusion we specify the different categories of phenomena contributing to a solar cycle.     

Ten cycles of solar and geomagnetic activity

Series of 110 years of sunspot numbers and indices of geomagnetic activity are used with 17 years of solar wind data in order to study through solar cycles both stream and shock event solar activity. According to their patterns on Bartels diagrams of geomagnetic indices, stable wind streams and transient solar activities are separated from each other. Two classes of stable streams are identified: equatorial streams occurring sporadically, for several months, during the main phase of sunspot cycles and both polar streams established, for several years, at each cycle, before sunspot minimum. Polar streams are the first activity of solar cycles. For study of the relationship between transient geomagnetic phenomena and sunspot activity, we raise the importance of the contribution, at high spot number, of severe storms and, at low spot number, of short lived and unstable streams. Solar wind data are used to check and complete the above results. As a conclusion, we suggest a unified scheme of solar activity evolution with a starting point every eleventh year, a total duration of 17 years and an overlapping of 6 years between the first and the last phase of both successive series of phenomena: first, from polar field reversal to sunspot minimum, a phase of polar wind activity of the beginning cycle is superimposed on the weak contribution of shock events of the ending cycle; secondly, an equatorial phase mostly of shock events is superimposed on a variable contribution of short lived and sporadic stable equatorial stream activities; and thirdly a phase of low latitude shock events is superimposed on the polar stream interval of the following cycle.     

22-year variations of the solar rotation and solar activity cycles

We have performed a comparative analysis of the results of our study of the 22-year rotation variations obtained from data on large-scale magnetic fields in the Hα line, magnetographic observations, and spectral-corona observations. All these types of data suggest that the rotation rate at low latitudes slows down at an epoch close to the maximum of odd activity cycles. The 22-year waves of rotation-rate deviation from the mean values drift from high latitudes toward the equator in a time comparable to the magnetic-cycle duration. We discuss the possibility of the generation of a solar magnetic cycle by the interaction of 22-year torsional oscillations with the slowly changing or relic magnetic field. We consider the generation mechanisms of the high-latitude magnetic field through a superposition of the magnetic fields produced by the decay and dissipation of bipolar groups and the relic or slowly changing magnetic field and a superposition of the activity wave from the next activity cycle at high latitudes.     

Approximation of 11-year solar cycles

We propose to approximate every 11-year cycle of solar activity by a function with three parameters. The first parameter determines the cycle position on the time axis, the second one shows the length of the growth phase of the activity index, and the third one is the maximum of smoothed index value. Values of these parameters for cycles 8–23 do not contradict in general the cycle parameters similar in sense and obtained from observations by the conventional method.     

The periodicity of solar activity cycles

On the basis of published Wolf Numbers and Schove Row, solar activity cycles in the interval of 11 to hundreds of years have been investigated. In this case the method of investigation of pulsating stars showing the Blazhko effect was applied. The elements of cycles and O-C were calculated and compared with results of solar activity parameters determined by classical methods.     

Peak years of various solar cycles

Using more extensive data than before, we have verified the 11-year, 60-year and ~250-year periods in solar activity and identified the peak years of these cycles.     

Multi-timescale solar cycles and the possible implications

Based on analysis of the annual averaged relative sunspot number (ASN) during 1700–2009, 3 kinds of solar cycles are confirmed: the well-known 11-yr cycle (Schwabe cycle), 103-yr secular cycle (numbered as G1, G2, G3, and G4, respectively since 1700); and 51.5-yr Cycle. From similarities, an extrapolation of forthcoming solar cycles is made, and found that the solar cycle 24 will be a relative long and weak Schwabe cycle, which may reach to its apex around 2012–2014 in the vale between G3 and G4. Additionally, most Schwabe cycles are asymmetric with rapidly rising-phases and slowly decay-phases. The comparisons between ASN and the annual flare numbers with different GOES classes (C-class, M-class, X-class, and super-flare, here super-flare is defined as ≥ X10.0) and the annal averaged radio flux at frequency of 2.84 GHz indicate that solar flares have a tendency: the more powerful of the flare, the later it takes place after the onset of the Schwabe cycle, and most powerful flares take place in the decay phase of Schwabe cycle. Some discussions on the origin of solar cycles are presented.     

Periodic behavior of solar flare index during solar cycles 20 and 21

Short-term periodicities of solar activity were studied with the flare index by using Discrete Fourier Transform for the time interval 1966–1986. Two noticeable periodicities (18.5 and 5 months) have been found. The existence of these periodicities comparing with the early findings is discussed.     

Dynamo-based scheme for forecasting the magnitude of solar activity cycles

In this paper we present a general framework for forecasting the smoothed maximum level of solar activity in a given cycle, based on a simple understanding of the solar dynamo. This type of forecasting requires knowledge of the Sun's polar magnetic field strength at the preceeding activity minimum. Because direct measurements of this quantity are difficult to obtain, we evaluate the quality of a number of proxy indicators already used by other authors which are physically related to the Sun's polar field. We subject these indicators to a rigorous statistical analysis, and specify in detail the analysis technique for each indicator in order to simplify and systematize reanalysis for future use. We find that several of these proxies are in fact poorly correlated or uncorrelated with solar activity, and thus are of little value for predicting activity maxima.We also present a scheme in which the predictions of the individual proxies are combined via an appropriately weighted mean to produce a compound prediction. We then apply the scheme to the current cycle 22, and estimate a maximum smoothed International sunspot number of 171 ± 26, which can be expressed alternatively as a smoothed 2800 MHz radio flux (F _10.7) of 211 ± 23 × (10^–22 Wm^–2Hz^–1), or as a smoothed sunspot area of 2660 ± 430 millionths of a solar disk. Once the actual maximum for cycle 22 has been established, we will have both additional statistics for all the proxy indicators, and a clearer indication of how accurately the present scheme can predict solar activity levels.     

The prediction method of similar cycles

The concept of degree of similarity(η),is proposed to quantitatively describe the similarity of a parameter(e.g.the maximum amplitude Rmax)of a solar cycle relative to a referenced one,and the prediction method of similar cycles is further developed.For two parameters,the solar minimum(Rmin)and rising rate(βa),which can be directly measured a few months after the minimum,a synthesis degree of similarity(ηs)is defined as the weighted-average of theηvalues around Rmin and βa,with the weights given by the coef...     

Prediction of solar cycle 24 and beyond

In the previous study (Hiremath, Astron. Astrophys. 452:591, 2006a), the solar cycle is modeled as a forced and damped harmonic oscillator and from all the 22 cycles (1755–1996), long-term amplitudes, frequencies, phases and decay factor are obtained. Using these physical parameters of the previous 22 solar cycles and by an autoregressive model, we predict the amplitude and period of the present cycle 23 and future fifteen solar cycles. The period of present solar cycle 23 is estimated to be 11.73 years and it is expected that onset of next sunspot activity cycle 24 might starts during the period 2008.57±0.17 (i.e., around May–September 2008). The predicted period and amplitude of the present cycle 23 are almost similar to the period and amplitude of the observed cycle. With these encouraging results, we also predict the profiles of future 15 solar cycles. Important predictions are: (i) the period and amplitude of the cycle 24 are 9.34 years and 110 (±11), (ii) the period and amplitude of the cycle 25 are 12.49 years and 110 (±11), (iii) during the cycles 26 (2030–2042 AD), 27 (2042–2054 AD), 34 (2118–2127 AD), 37 (2152–2163 AD) and 38 (2163–2176 AD), the sun might experience a very high sunspot activity, (iv) the sun might also experience a very low (around 60) sunspot activity during cycle 31 (2089–2100 AD) and, (v) length of the solar cycles vary from 8.65 years for the cycle 33 to maximum of 13.07 years for the cycle 35.     

DeepSun:machine-learning-as-a-service for solar flare prediction

Solar flare prediction plays an important role in understanding and forecasting space weather.The main goal of the Helioseismic and Magnetic Imager(HMI), one of the instruments on NASA's Solar Dynamics Observatory, is to study the origin of solar variability and characterize the Sun's magnetic activity.HMI provides continuous full-disk observations of the solar vector magnetic field with high cadence data that lead to reliable predictive capability; yet, solar flare prediction effort utilizing these data is still limited. In this paper, we present a machine-learning-as-a-service(MLaa S) framework, called Deep Sun,for predicting solar flares on the web based on HMI's data products. Specifically, we construct training data by utilizing the physical parameters provided by the Space-weather HMI Active Region Patch(SHARP)and categorize solar flares into four classes, namely B, C, M and X, according to the X-ray flare catalogs available at the National Centers for Environmental Information(NCEI). Thus, the solar flare prediction problem at hand is essentially a multi-class(i.e., four-class) classification problem. The Deep Sun system employs several machine learning algorithms to tackle this multi-class prediction problem and provides an application programming interface(API) for remote programming users. To our knowledge, Deep Sun is the first MLaa S tool capable of predicting solar flares through the internet.     

The properties of solar active regions responsible for ground level enhancements during solar cycles 22 and 23

This is a study designed to analyze the relationship between ground level enhancements（GLEs）and their associated solar active regions during solar cycles 22and 23.Results show that 90.3%of the GLE events that are investigated are accompanied by X-class flares,and that 77.4%of the GLE events originate from super active regions.It is found that the intensity of a GLE event is strongly associated with the specific position of an active region where the GLE event occurs.As a consequence,the GLE events having a peak increase rate exceeding 50%occur in a longitudinal range from W20 to W100.Moreover,the largest GLE events occur in a heliographic longitude at roughly W60.Additionally,an analysis is made to understand the distributional pattern of the Carrington longitude of the active regions that have generated the GLE events.