Predicting the 25th solar cycle using deep learning methods based on sunspot area data

It is a significant task to predict the solar activity for space weather and solar physics. All kinds of approaches have been used to forecast solar activities, and they have been applied to many areas such as the solar dynamo of simulation and space mission planning. In this paper, we employ the long-shortterm memory(LSTM) and neural network autoregression(NNAR) deep learning methods to predict the upcoming 25 th solar cycle using the sunspot area(SSA) data during the period of May 1874 to December2020. Our results show that the 25 th solar cycle will be 55% stronger than Solar Cycle 24 with a maximum sunspot area of 3115±401 and the cycle reaching its peak in October 2022 by using the LSTM method. It also shows that deep learning algorithms perform better than the other commonly used methods and have high application value.

Statistical study on great geomagnetic storms during solar cycle 23

Characteristics of great geomagnetic storms during solar cycle 23 were statistically investigated. Firstly, we focused on the uniqueness of solar cycle 23 by analyzing both the great storm number and sunspot number from 1957 to 2008. It was found that the relationship between the sunspot number and great storm number weakened as the activity of the storms strengthened. There was no obvious relationship between the annual sunspot number and great storm number with Dst≤-300 nT. Secondly, we studied the relationship between the peak Dst and peak Bz in detail. It was found that the condition Bz〈-10 nT is not necessary for storms with Dst≤-100 nT, but seems necessary for storms with Dst≤-150 nT. The duration for Bz≤-10 nT has no direct relationship with the giant storm. The correlation coefficient between the Dst peak and Bz peak for the 89 storms studied is 0.81. After removing the effect of solar wind dynamic pressure on the Dst peak, we obtained a better correlation coefficient of 0.86. We also found the difference between the Dst peak and the corrected Dst peak was proportional to the Dst peak.

The Additional Criterion for the Determination of the Time of Minimum of a Solar Cycle

The sunspot number is becoming an increasingly insufficiently reliable parameter for the determination of the time of minimum of a solar cycle during the prolonged and deep minimum of the 23rd solar cycle. Moreover, the sunspot number does not quantitatively reflect physical processes and is a practically conventional qualitative “noisy” parameter. Introduction of an additional criterion for the determination of the time of minimum of a solar cycle is becoming particularly topical due to the upcoming common descent of the level of the 2-secular cycle, when the amplitude of sunspot activity variation will sequentially decrease during several subsequent cycles (after the 23rd cycle). We propose the adoption of the smoothed minimal level of the total solar irradiance (TSI) as an additional physically justified criterion for the determination of the time of minimum of a solar cycle during the minimum of sunspot activity. The minimal level of the monthly average values of the TSI smoothed for 13 months when the last two of its values exceed the preceding value at the point of minimum will additionally indicate the time of minimum of a cycle. The additional criterion has been successfully used for the determination of the time of minima of the preceding 21st and 22nd cycles.

Periodicity of sunspot activity in the modern solar cycles

Sunspot number, sunspot area and sunspot unit area are usually used to show sunspot activity. In this paper, periodicity of sunspot activity of modern solar cycles has been investigated through analyzing the monthly mean val- ues of the three indices in the time interval of May 1874 to May 2004 by use of the wavelet transform. Their global power spectra and local power spectra are given while the statistical tests of these spectra are taken into account. The main results are (1) the local wavelet power spectrum of the sunspot number seems like that of the sunspot area, indicat- ing that the periodicity of the both indices is similar. The local power spectrum of the sunspot unit area resembles the local power spectra of the previous two indices, but looks more complicated. (2) the possible periods in sunspot activity are about 10.6 (or 10.9 years for the sunspot unit area), 31, and 42 years, and the period of about 10.6 years is statisti- cally significant in the considered time. For the periods of about 31 and 42 years, their power peaks are under the 95% confidence level line but over the mean red-noise spectral line, and for the other rest periods, their power peaks are even under the mean red-noise spectral line, which are sta- tistically insignificant. (3) the local power of the three periods is higher in the late stage than in the early stage of the con- sidered time. (4) the period characteristics of the three indi- ces, shown in the global power spectra and the local power spectra, are similar but there is difference in detail.

The Dependence between Solar Flare Emergence and the Average Background Solar X-Ray Flux Emission

Solar flares, sudden bursts of intense electromagnetic radiation from the Sun, can significantly disrupt technological infrastructure, including communication and navigation satellites. To mitigate these risks, accurate forecasting of solar activity is crucial. This study investigates the potential of the Sun’s background X-ray flux as a tool for predicting solar flares. We analyzed data collected by solar telescopes and satellites between the years 2013 and 2023, focusing on the duration, frequency, and intensity of solar flares. We compared these characteristics with the background X-ray flux at the time of each flare event. Our analysis employed statistical methods to identify potential correlations between these solar phenomena. The key finding of this study reveals a significant positive correlation between solar flare activity and the Sun’s background X-ray flux. This suggests that these phenomena are interconnected within the framework of overall solar activity. We observed a clear trend: periods with increased occurrences of solar flares coincided with elevated background flux levels. This finding has the potential to improve solar activity forecasting. By monitoring background flux variations, we may be able to develop a more effective early warning system for potentially disruptive solar flares. This research contributes to a deeper understanding of the complex relationship between solar flares and the Sun’s overall radiative output. These findings indicate that lower-resolution X-ray sensors can be a valuable tool for identifying periods of increased solar activity by allowing us to monitor background flux variations. A more affordable approach to solar activity monitoring is advised.

Has the maximum of Solar Cycle 23 appeared?

In this note, we define firstly a compositive parameter as an index describing the level of solar activity in a solar cycle. The parameter is derived from a combination of the smoothed monthly mean sunspot number with the fluctuation of the associated monthly mean sunspot numbers to the smoothed one. Then, a method is developed for estimating the time of the appearance of a solar maximum based on the conception of similar cycles. An application ofthe method to the 23rd solar cycle shows that the maximum of the cycle should have appeared in the period from April to August 2000, and the descending phase of Cycle 23 has come.

Normalization of sunspot cycles and eigen mode analysis

The smoothed monthly sunspot numbers of the previous 22 complete sunspot cycles are normalized in time domain, and then an eigen mode analysis is carried out to draw the principle factors (or components) in the cycles. The results show that the main characteristics of the solar cycles can be described fairly well by the first 5 eigen modes. The obtained eigen modes are used to predict the declining phase of cycle 23 on the basis of the data prior to its maximum. The prediction indicates that cycle 23 will last for 127 months to December 2006, with the minimum of 6.2.

A method to predict amplitude and date of maximum sunspot number

A method to predict the amplitude and date of the maximum sunspot number is introduced. The regression analysis of the relationship between the variation rate of monthly sunspot numbers in the initial stage of solar cycles and both of the maximum and the time-length of ascending period of the cycle showed that they are closely correlative. In general, the maximum will be larger and the ascending period will be shorter when the rate is larger. The rate of sunspot numbers in the initial 2 years of the 23rd cycle is thus analyzed based on these grounds and the maximum of the cycle is predicted. For the smoothed monthly sunspot numbers, the maximum will be about 139.2 ±18.8 and the time-length of ascending period will be about 3.31 ±0.42 years, that is to say, the maximum will appear around the spring of the year 2000. For the mean monthly ones, the maximum will be near 170.1±22.9 and the time-length of ascending period will be about 3.42 ±0.46 years, that is to say, the appearing date of the maximum

基于小波变换的郑州降雨量与太阳黑子活动关系分析

为探究太阳黑子活动与地区降雨量的关联性,采用连续小波变换方法,分析了1980年以来郑州地区(新郑站点)降雨量和太阳黑子数的数据变化,并对不同时段两者的相关性进行研究;进一步对两者进行交叉小波变换和小波相干谱分析,并根据两者关系通过太阳黑子数观测值对降雨量进行预测。结果表明:(1)不同时段降雨量和太阳黑子数的相关性存在正负差异的现象。降雨量的第一主周期尺度是21 a,在此主周期尺度下得到14 a主周期;太阳黑子数的第一主周期尺度是16 a,在此主周期尺度下得到11 a主周期(与经验值相符)。降雨量与太阳黑子数的主周期相差了3 a,因此导致两者的相关性在不同时段存在正负差异。(2)降雨量与太阳黑子数在1992—2008年的8~12 a时间尺度上关联性显著,且降雨量比太阳黑子数存在规律性的时间滞后,两者在2~4 a和7~10 a的时间尺度上关联性较好;降雨量比太阳黑子数分别在1991—2004年和2006—2013年这两个时间段上呈现规律性的滞后,两者在其他时间段的各时间尺度上关联性不明显。(3)根据延迟年数经验公式,由太阳黑子数观测值对降雨量进行预测,最近的降雨量峰年在2022年附近,与2021年郑州“7·20”特大暴雨的发生时间相近,而下一个降雨量极小年在2028年前后,且随着时间的推移极端旱涝情况可能会愈加严重。

Starspots, stellar cycles and stellar flares： Lessons from solar dynamo models

In this review, we discuss whether the present solar dynamo models can be extrapolated to explain various aspects of stellar activity. We begin with a summary of the following kinds of data for solar-like stars:(i) data pertaining to stellar cycles from Ca H/K emission over many years;(ii) X-ray data indicating hot coronal activity;(iii) starspot data(especially about giant polar spots); and(iv) data pertaining to stellar superflares. Then we describe the current status of solar dynamo modelling—giving an introduction to the flux transport dynamo model, the currently favoured model for the solar cycle. While an extrapolation of this model to solar-like stars can explain some aspects of observational data, some other aspects of the data still remain to be theoretically explained. It is not clear right now whether we need a different kind of dynamo mechanism for stars having giant starspots or producing very strong superflares.

中国西部及邻区百年尺度周期的地震活动及其和太阳活动之间的负相关性

利用小波变换分析中国西部及邻区1700年以来M≥7级和M-T图分析1700年以来M≥7.8级地震活动,除了得到和其他学者研究基本一致的几个十年尺度周期结果外,还得到百年左右尺度的地震活动周期结果,再与太阳黑子活动进行比较,发现地震活动与太阳黑子数在百年左右尺度周期上具有负相关性,地震高活动时段对应太阳黑子低值时段.此外,从活动性分析中得到目前中国西部及邻区可能正处于强震活跃期间.

青海德令哈地区近400年来的降水量变化与太阳活动

使用多种数学统计方法分析了德令哈地区降水量变化与太阳活动之间的关系,发现近 400年来降水量的长期变化与太阳黑子周期长度(SCL)和太阳黑子周期上升支长度之间存在着较好的反相关关系,当SCL偏短、太阳黑子周期上升支长度偏短时,太阳活动偏强,德令哈地区降水量偏多,反之偏少。功率谱和小波分析发现降水量序列中存在着与太阳活动的多种周期相一致的周期,对降水量与太阳活动在不同时间尺度上周期变化之间的关系进行了详细分析。交叉小波分析发现太阳活动主要在百年左右尺度的周期变化上影响德令哈地区降水量的长期变化,太阳活动周期变化的信号越强,对降水量变化的影响越大。文章最后对太阳活动影响德令哈地区降水量变化的可能机制进行了探讨。

长江、黄淮流域近期特大洪水预警和防洪形势

根据太阳黑子活动和长江、黄淮流域１８４０～１９９４年历史和实测的洪水资料，推断在１９９７年及其前后，长江、黄淮流域很有可能出现一次特大的洪水。同时指出，目前长江、淮河、黄河的防洪形势不容乐观，必须及早采取对策，确保人民生命和财产的安全。

太阳绕太阳系质心运动22年周期及其与太阳活动的联系

对于太阳活动22年周期的成因机制长期存在着争论.本文借助于行星会合指数以及开普勒第三定律,对太阳绕太阳系质心运动周期进行了分析计算.结果发现,太阳绕太阳系质心运动存在22.1826年显著周期,这与太阳磁场变化的22.20年周期相吻合.并从太阳系角动量守恒的角度解释了两者之间的成因联系:在太阳绕太阳系质心运动的准22年周期中,太阳系质心与太阳质心逐步接近而后逐步分离.当两个质心之间的距离接近零的时候,太阳轨道角动量与自转角动量叠加,会导致太阳自转角速度的加快;当两个质心之间的距离逐渐远离的时候,则导致太阳自转角速度的减慢.这可能是引发太阳活动和太阳磁场变化的原因.这一新认识为太阳活动准22年周期成因机制的解释提供了新的线索和依据.

21、22、23太阳活动周上升期太阳黑子资料的分析

本文分析了第２１ 、２２ 、２３ 太阳活动周的上升期２３ 个月（ 月均值） 太阳黑子资料。结果表明：太阳黑子相对数和面积南北不对称。２３ 周的太阳黑子相对数和面积（２３ 个月的平均） 高于２２ 周，但低于２１ 周。我们估计第２３ 周峰年为２０００ 年３ 月或１９９９ 年１２ 月。

太阳22周峰年若干特点

本文讨论了第２２太阳活动周的下列重要特点：１．呈现双峰，并在双峰期的槽中又突起孤立的单峰。２．黑子面积峰值滞后相对数峰值的仅占１６．６７％；黑子面积与相对数同步占５８．３３％；二者峰值不能对应占２５％。３．１９８６年１０月以后，纬度≥３０°的有半影的黑子群共出现８７群；延迟在峰年期间出现的有５３群，占６０．９２％；对应有Ｍ级以上Ｘ射线爆发的活动区１８个，占２０．６９％。这一现象与“蝴蝶图”规律不符。

太阳黑子的世纪周期及对24、25活动周的预报

太阳活动除了具有公认的11a周期以外,还存在着一个80～120 a变化的世纪周期,也称为Gleissberg周期。使用傅里叶变换和小波分析的方法,分析了1700～2008年的年均黑子数世纪周期的变化规律。得到结果:在太阳活动世纪周期的低谷期,所对应11 a太阳周的极大年和极小年的黑子数目都比其他太阳周的低。在这300多年里,世纪周期的周期长度也有变化。由世纪周期的变化趋势,预测第24、25太阳活动周将处于世纪周期的低谷期。通过对以前3个世纪周期的谷期黑子数求平均的方法,得到第24、25太阳周极大年年均黑子数为63.6±21.1,极小年的为2.2±2.1。这些结果有助于理解当前太阳活动反常宁静这一现象。

第23至24周太阳质子事件的统计特征

第23至24太阳活动周(1997-2016年)期间太阳质子事件的强度统计分析表明,1997-2016年期间总共发生了128个太阳质子事件,其中峰值通量范围为10~99 pfu,100~999 pfu,1000~2999 pfu及>3000 pfu的事件分别占55.15%,27.94%,9.56%,7.35%.太阳质子事件的不对称性分析表明,不同强度太阳质子事件东西不对称性的程度不相同,其中1000~2999pfu事件的不对称性最强,而3000pfu以上事件的不对称性最弱.第23周期间,太阳质子事件主要发生在太阳活动周两个峰值之间和最大峰值之后的口时段,而第24周太阳质子事件主要发生在太阳活动周最大峰值之前.

阜新夏季异常降水在太阳活动周期的规律研究

利用1951-2015年太阳黑子相对数和阜新夏季降水,分析研究了基于太阳活动周期的阜新夏季异常降水规律。结果表明:太阳活动周期内阜新夏季异常降水偏多年略多于夏季降水异常偏少年;夏季异常降水距平百分率极大值为99.5%,极小值为-52.7%;太阳黑子谷值年周期内阜新夏季降水异常偏多和偏少年发生几率均比太阳黑子峰值年周期内的大;夏季降水异常偏多年最大几率为0.6,异常偏少年最大几率为0.67;太阳黑子峰值年周期内的M、M+1年多连续发生夏季降水异常偏少;太阳黑子谷值年周期内的m-1、m年多连续发生夏季降水异常偏多;太阳黑子峰值年周期内阜新夏季平均降水量的最小值年在M年;太阳黑子谷值年周期内阜新夏季平均降水量的最大值年在m-1年;太阳活动周期内阜新夏季降水量存在2~3年的准周期变化;阜新夏季降水的准对称轴在太阳黑子峰值年(M)、谷值年(m)附近;太阳活动周期内的阜新夏季平均降水量与太阳黑子相对数成反相关;太阳黑子峰值年后少雨向多雨转折年平均在M+2年;太阳黑子谷值年后多雨向少雨转折年平均在m+3年。

低轨道卫星表面电位探测器探测数据分析

目的了解太阳活动低年低轨道卫星表面充电的特征规律,为今后低轨道卫星表面充电的防护设计提供参考。方法利用我国一颗低轨道卫星搭载的表面电位探测器数据,对探测到的2017—2019年的78次表面充电事件进行统计分析。重点研究78次事件的充电时长、电位峰值、时空分布等特征以及事件与地磁活动的关系。结果在太阳活动低年,83.3%表面充电事件持续时间不超过1min,80.7%表面充电事件的充电峰值绝对值不超过100 V;97.4%的事件出现在南半球高纬度地区;88.5%的事件发生在磁地方时的18至02时之间;当表面充电事件发生率不为0时,事件发生率和Kp指数的相关系数为0.97。结论在太阳活动低年,表面充电事件的持续时间较短,并且强度不大。表面充电事件发生位置具有明显的南北不对称性,呈现南多北少的趋势。表面充电事件多发生于高纬度地区,在磁地方时的傍晚至午夜发生概率高。表面充电事件发生率和地磁活动具有较好的相关性。