The Sunspots

In the present paper, the theoretical frame work of magneto hydrodynamics (MHD) is used to give a solution of the problem about the origin, persistence and disappearance of the Sunspots;as well as their tendency to appear as bipolar magnetic couples. According to the results obtained, a possible explanation about the change of polarity in both solar hemispheres is given. Heuristic but logical arguments about the periodicity of the phenomenon of the observed magnetic polarity and the tendency of couples of Sunspots to appear solely in certain latitudes that can be called tropical regions of the Sun are presented. Finally, an indirect experimental test is proposed to show the possible process that produces the polarity of the Sunspots in a given cycle, as well as the invertion of that polarity in the next solar cycle.

The Formation and Evolution of the Sun and the Source of Star Energy as Well as the Sunspots and Flares of the Sun

Nebula theory is the most widely accepted hypothesis about the formation and evolution of the Solar System. This theoryholds that the Sun is formed from a collapsed gas cloud 4.57 billion years ago;when the core temperature of the gas cloud rises to 10million K, the thermonuclear reaction of hydrogen fusion into helium is ignited, then the Sun become a star;once the hydrogen in thecore is exhausted, the life of the star will end. But the limited hydrogen element obviously cannot satisfy such a long-termthermonuclear reaction, in order to sustain long-term thermonuclear reactions, a steady stream of fuel must be obtained from space.So the existing hypothesis about the formation and evolution of the Solar System has serious defects. Thus the author has studied theformation of the Moon, the Earth and the Sun, and discovered the formation of the Sun and the real source of star energy. The authorcould also explain many solar activity phenomena such as sunspots, flares, prominences, etc.

Using Optimized Distributional Parameters as Inputs in a Sequential Unsupervised and Supervised Modeling of Sunspots Data

Detecting naturally arising structures in data is central to knowledge extraction from data. In most applications, the main challenge is in the choice of the appropriate model for exploring the data features. The choice is generally poorly understood and any tentative choice may be too restrictive. Growing volumes of data, disparate data sources and modelling techniques entail the need for model optimization via adaptability rather than comparability. We propose a novel two-stage algorithm to modelling continuous data consisting of an unsupervised stage whereby the algorithm searches through the data for optimal parameter values and a supervised stage that adapts the parameters for predictive modelling. The method is implemented on the sunspots data with inherently Gaussian distributional properties and assumed bi-modality. Optimal values separating high from lows cycles are obtained via multiple simulations. Early patterns for each recorded cycle reveal that the first 3 years provide a sufficient basis for predicting the peak. Multiple Support Vector Machine runs using repeatedly improved data parameters show that the approach yields greater accuracy and reliability than conventional approaches and provides a good basis for model selection. Model reliability is established via multiple simulations of this type.

Latitudinal migration of sunspots based on the ESAI database

The latitudinal migration of sunspots toward the equator,which implies there is propagation of the toroidal magnetic flux wave at the base of the solar convection zone,is one of the crucial observational bases for the solar dynamo to generate a magnetic field by shearing of the pre-existing poloidal magnetic field through differential rotation.The Extended time series of Solar Activity Indices（ESAI）elongated the Greenwich observation record of sunspots by several decades in the past.In this study,ESAI＇s yearly mean latitude of sunspots in the northern and southern hemispheres during the years 1854 to 1985 is utilized to statistically test whether hemispherical latitudinal migration of sunspots in a solar cycle is linear or nonlinear.It is found that a quadratic function is statistically significantly better at describing hemispherical latitudinal migration of sunspots in a solar cycle than a linear function.In addition,the latitude migration velocity of sunspots in a solar cycle decreases as the cycle progresses,providing a particular constraint for solar dynamo models.Indeed,the butterfly wing pattern with a faster latitudinal migration rate should present stronger solar activity with a shorter cycle period,and it is located at higher latitudinal position,giving evidence to support the Babcock-Leighton dynamo mechanism.

CORRELATION ANALYSIS OF FOREST FIRES AND SUNSPOTS

This paper analyses the relationship of forest fires and sunspots in Hcilongjiang Province in the past 40 ycars(1950-1989). The results indicated that each of the forest fire indexes such as forest Fire rate(y1), times of forest firc(Y2), average forest fire area for one time Y4 (equals the Y5 / Y2) and total forest fire arca(Y5) has a negative correlation with mean annual relative sunspots of the same year; total times of forest fire inside and outside of forest stands( Y3) has a positive correlation with sunspots. The 5 indexes stated above has a similar relation to last year's mean annual relative sunspots.

Sunspot Group Detection and Classification by Dual Stream Convolutional Neural Network Method

The automatic detection and analysis of sunspots play a crucial role in understanding solar dynamics and predicting space weather events.This paper proposes a novel method for sunspot group detection and classification called the dual stream Convolutional Neural Network with Attention Mechanism(DSCNN-AM).The network consists of two parallel streams each processing different input data allowing for joint processing of spatial and temporal information while classifying sunspots.It takes in the white light images as well as the corresponding magnetic images that reveal both the optical and magnetic features of sunspots.The extracted features are then fused and processed by fully connected layers to perform detection and classification.The attention mechanism is further integrated to address the“edge dimming”problem which improves the model’s ability to handle sunspots near the edge of the solar disk.The network is trained and tested on the SOLAR-STORM1 data set.The results demonstrate that the DSCNN-AM achieves superior performance compared to existing methods,with a total accuracy exceeding 90%.

Astral Actions on Allais’ Pendulum Apparently Inexplicable by Classical Factors: A Point of the Situation

1) The observation by Allais of the precession of pendulums from 1954 to 1960 highlighted regularities of astral origin an in-depth analysis of which showed that, apparently, no classical phenomenon can explain them. These regularities were diurnal waves whose periods are characteristic of astral influence (the main ones being 24 h and 24 h 50 min), annual and semi-annual components, and a multi-annual component of approximately 6 years, an influence of Jupiter being a very good candidate to explain it. 2) Allais had experimentally established that all these astral influences were expressed globally on the pendulum by an action tending to call back its plane of oscillation towards a direction variable in time, and which ovalized its trajectory. In 2019 the observation of 2 pendulums in Horodnic (Romania), thanks to the use of an automatic alidade, made it possible to identify the main mechanism that, very probably, acted on the pendulum to achieve this result. This perturbation model, called “linear anisotropy”, is characterized by its “coefficient of anisotropy” η, and by the azimuth of its “direction of anisotropy”. The composition of 2 linear anisotropies is always a linear anisotropy. 3) In the search for the phenomena which could be at the origin of all what precedes, the fact that they must create an ovalization immediately eliminates some of them. 4) We have calculated the values of η corresponding to the 24 h and 24 h 50 min waves both for the observations in Horodnic and the Allais observations. The order of magnitude (some 10−7) is effectively the same in both cases. 5) Mathematically, the regularities discovered may result of a new force field but also, as Allais proposes, from the creation, under the astral influences, of a local anisotropy of the medium in which the pendulum oscillates. In the first case the length of the pendulum is involved, in the second one not. The data available do not make it possible to decide. 6) The joint exploitation, in mechanics and optics, of Allais observations and of observations by other experimenters provides additional information: a) Allais, and after him several other scientists, discovered also marked anomalies in the precession of pendulums during certain eclipses, and maybe certain other syzygies. For the few eclipses for which both something was observed and sufficient data were available (one of them being a lunar eclipse for which nothing had been published until now), it was always the above perturbation model which acted on the pendulum, but sometimes with quite exceptional magnitude. b) There are quite possible links with optics. During the observation campaign of August 1958, which had implemented both two pendulums and an optical device, all the 24 h 50 min waves were almost in phase. In the precession of the Allais pendulum, in Miller’s interferometric observations in Mont Wilson, and in Esclangon’s observations in Strasbourg, a same peculiarity is found: the extrema of the annual influence are at the equinoxes, not at the solstices.

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.

Flare Forecast Model Based on DS-SMOTE and SVM with Optimized Regular Term

The research of flare forecast based on the machine learning algorithm is an important content of space science.In order to improve the reliability of the data-driven model and weaken the impact of imbalanced data set on its forecast performance,we proposes a resampling method suitable for flare forecasting and a Particle Swarm Optimization(PSO)-based Support Vector Machine(SVM)regular term optimization method.Considering the problem of intra-class imbalance and inter-class imbalance in flare samples,we adopt the density clustering method combined with the Synthetic Minority Over-sampling Technique(SMOTE)oversampling method,and performs the interpolation operation based on Euclidean distance on the basis of analyzing the clustering space in the minority class.At the same time,for the problem that the objective function used for strong classification in SVM cannot adapt to the sample noise,In this research,on the basis of adding regularization parameters,the PSO algorithm is used to optimize the hyperparameters,which can maximize the performance of the classifier.Finally,through a comprehensive comparison test,it is proved that the method designed can be well applied to the flare forecast problem,and the effectiveness of the method is proved.

Research Progress on Solar Flare Forecast Methods Based on Data-driven Models

Eruption of solar flares is a complex nonlinear process,and the rays and high-energy particles generated by such an eruption are detrimental to the reliability of space-based or ground-based systems.So far,there are not reliable physical models to accurately account for the flare outburst mechanism,but a lot of data-driven models have been built to study a solar flare and forecast it.In the paper,the status of solar-flare forecasting is reviewed,with emphasis on the machine learning methods and data-processing techniques used in the models.At first,the essential forecast factors strongly relevant to solar flare outbursts,such as classification information of the sunspots and evolution pattern of the magnetic field,are reviewed and analyzed.Subsequently,methods of resampling for data preprocessing are introduced to solve the problems of class imbalance in the solar flare samples.Afterwards,typical model structures adopted for flare forecasting are reviewed from the aspects of the single and fusion models,and the forecast performances of the different models are analyzed.Finally,we herein summarize the current research on solar flare forecasting and outline its development trends.

The Decay Process of an α-configuration Sunspot

The decay of sunspot plays a key role in magnetic flux transportation in solar active regions(ARs).To better understand the physical mechanism of the entire decay process of a sunspot,an α-configuration sunspot in AR NOAA 12411 was studied.Based on the continuum intensity images and vector magnetic field data with stray light correction from Solar Dynamics Observatory/Helioseismic and Magnetic Imager,the area,vector magnetic field and magnetic flux in the umbra and penumbra are calculated with time,respectively.Our main results are as follows:(1) The decay curves of the sunspot area in its umbra,penumbra,and whole sunspot take the appearance of Gaussian profiles.The area decay rates of the umbra,penumbra and whole sunspot are-1.56 MSH day^(-1),-12.61 MSH day^(-1) and-14.04 MSH day^(-1),respectively;(2) With the decay of the sunspot,the total magnetic field strength and the vertical component of the penumbra increase,and the magnetic field of the penumbra becomes more vertical.Meanwhile,the total magnetic field strength and vertical magnetic field strength for the umbra decrease,and the inclination angle changes slightly with an average value of about 20°;(3) The magnetic flux decay curves of the sunspot in its umbra,penumbra,and whole sunspot exhibit quadratic patterns,their magnetic flux decay rates of the umbra,penumbra and whole sunspot are-9.84 × 10^(19)Mx day^(-1),-1.59 × 10^(20)Mx day^(-1) and -2.60 × 10^(20)Mx day^(-1),respectively.The observation suggests that the penumbra may be transformed into the umbra,resulting in the increase of the average vertical magnetic field strength and the reduction of the inclination angle in the penumbra during the decay of the sunspot.

Variation of Small Scale Magnetic Fields Over a Century using Ca-K Images as Proxy

A combined uniform and long-time series of Ca-K images from the Kodaikanal Observatory,Mount Wilson Observatory and Mauna Loa Solar Observatory was used to identify and study the Ca-K small-scale features and their solar cycle variations over a century.The small scale features are classified into three distinct categories:enhanced network,active network and quiet network.All these features show that their areas vary according to the11 yr solar cycle.The relative amplitude of the Ca-K network variations agrees with that of the sunspot cycle.The total area of these small-scale features varies from about 5%during the minimum phase of the solar cycle to about20%during its maximum phase.

A Comparison of Co-temporal Vector Magnetograms Obtained with HMI/SDO and SP/Hinode

Accurate measurement of magnetic fields is very important for understanding the formation and evolution of solar magnetic fields.Currently,there are two types of solar magnetic field measurement instruments:filter-based magnetographs and Stokes polarimeters.The former gives high temporal resolution magnetograms and the latter provides more accurate measurements of magnetic fields.Calibrating the magnetograms obtained by filter-based magnetographs with those obtained by Stokes polarimeters is a good way to combine the advantages of the two types.Our previous studies have shown that,compared to the magnetograms obtained by the Spectro-Polarimeter(SP)on board Hinode,those magnetograms obtained by both the filter-based Solar Magnetic Field Telescope(SMFT)of the Huairou Solar Observing Station and by the filter-based Michelson Doppler Imager(MDI)aboard SOHO have underestimated the flux densities in their magnetograms and systematic center-to-limb variations present in the magnetograms of both instruments.Here,using a sample of 75 vector magnetograms of stable alpha sunspots,we compare the vector magnetograms obtained by the Helioseismic and Magnetic Imager(HMI)aboard Solar Dynamics Observatory(SDO)with co-temporal vector magnetograms acquired by SP/Hinode.Our analysis shows that both the longitudinal and transverse flux densities in the HMI/SDO magnetograms are very close to those in the SP/Hinode magnetograms and the systematic center-to-limb variations in the HMI/SDO magnetograms are very minor.Our study suggests that using a filter-based magnetograph to construct a low spectral resolution Stokes profile,as done by HMI/SDO,can largely remove the disadvantages of the filter-type measurements and yet still possess the advantage of high temporal resolution.

Periodicities in Solar Activity, Solar Radiation and Their Links with Terrestrial Environment

Solar magnetic activity is expressed via variations of sunspots and active regions varying on different timescales. The most accepted is an 11-year period supposedly induced by the electromagnetic solar dynamo mechanism. There are also some shorter or longer timescales detected: the biennial cycle (2 - 2.7 years), Gleisberg cycle (80 - 100 years), and Hallstatt’s cycle (2100 - 2300 years). Recently, using Principal Component Analysis (PCA) of the observed solar background magnetic field (SBMF), another period of 330 - 380 years, or Grand Solar Cycle (GSC), was derived from the summary curve of two eigenvectors of SBMF. In this paper, a spectral analysis of the averaged sunspot numbers, solar irradiance, and the summary curve of eigenvectors of SBMF was carried out using Morlet wavelet and Fourier transforms. We detect a 10.7-year cycle from the sunspots and modulus summary curve of eigenvectors as well a 22-year-cycle and the grand solar cycle of 342 - 350-years from the summary curve of eigenvectors. The Gleissberg centennial cycle is only detected on the full set of averaged sunspot numbers for 400 years or by adding a quadruple component to the summary curve of eigenvectors. Another period of 2200 - 2300 years is detected in the Holocene data of solar irradiance measured from the abundance of 14C isotope. This period was also confirmed with the period of about 2000 - 2100 years derived from a baseline of the solar background magnetic field, supposedly, caused by the solar inertial motion (SIM) induced by the gravitation of large planets. The implication of these findings for different deposition of solar radiation into the northern and southern hemispheres of the Earth caused by the combined effects of the solar activity and solar inertial motion on the terrestrial atmosphere is also discussed.

Determination of Solar Radius and Earth’s Radius by Relativistic Matter Wave

In recent years, relativistic matter waves have been applied to the solar system to explain some quantum gravity effects. This paper shows that the solar size and Earth’s size are the consequences of Bode’s rule in terms of the relativistic matter wave. The solar radius is determined as 7e+8 (m) with a relative error of 0.72%;the Earth’s radius is determined as 6.4328e+6 (m) with a relative error of 0.86%. The Earth’s atmospheric circulation is also investigated in terms of the relativistic matter wave, the wind fields on the Earth’s surface are calculated, and the results agree well with experimental observation. These findings indicate that the solar system is under the control of the planetary relativistic matter waves.

Investigation of a Possible Link between Solar Activity and Climate Change in Saudi Arabia: Rainfall Patterns

In this study, annual, quarterly, and monthly mean precipitation data in Saudi Arabia were correlated with sunspot number (SSN) and galactic cosmic ray (CR) flux over 35 years (1985-2019). The results show that the strength, magnitude, proportion and statistical significance of the relationship between precipitation and the two variables varied by season and month. We find that mean annual precipitation in Saudi Arabia, from May to November, and summer and autumn are correlated with cosmic rays and inversely correlated with SSN. Correlations of varying intensities and scales were found during the remaining months and during winter and spring. The relationships between the rainfall and SSN and CR for each solar cycle were investigated and showed that for all three cycles, the annual rainfall over Saudi Arabia has a positive correlation with CR. Different results were obtained when the seasonal rainfall data correlated with the SSNs and CRs during each cycle. The results obtained, in terms of their strength and magnitude, are affected by terrestrial and extra-terrestrial factors. These factors have been briefly presented and discussed. These findings represent a step towards understanding the possible role of solar activity in climate change for future meteorological phenomenon forecasting, even if the physical mechanism is still poorly quantified.

The Effect of Solar Activity on the Annual Precipitation in the Beijing Area

Using continuous wavelet transform, we examine the relationship between solar activity and the annual precipitation in the Beijing area. The results indicate that the annual precipitation is closely related to the variation of sunspot numbers, and that solar activity probably plays an important role in influencing the precipitation on land.

A Running Average Method for Predicting the Size and Length of a Solar Cycle

The running correlation coefficient between the solar cycle amplitudes and the max-max cycle lengths at a given cycle lag is found to vary roughly in a cyclical wave with the cycle number, based on the smoothed monthly mean Group sunspot numbers available since 1610. A running average method is proposed to predict the size and length of a solar cycle by the use of the varying trend of the coefficients. It is found that, when a condition （that the correlation becomes stronger） is satisfied, the mean prediction error （16.1） is much smaller than when the condition is not satisfied （38.7）. This result can be explained by the fact that the prediction must fall on the regression line and increase the strength of the correlation. The method itself can also indicate whether the prediction is reasonable or not. To obtain a reasonable prediction, it is more important to search for a running correlation coefficient whose varying trend satisfies the proposed condition, and the result does not depend so much on the size of the correlation coefficient. As an application, the peak sunspot number of cycle 24 is estimated as 140.4 ± 15.7, and the peak as May 2012 ±11 months.

The Prediction of Maximum Amplitudes of Solar Cycles and the Maximum Amplitude of Solar Cycle 24

We present a brief review of predictions of solar cycle maximum amplitude with a lead time of 2 years or more. It is pointed out that a precise prediction of the maximum amplitude with such a lead-time is still an open question despite progress made since the 1960s. A method of prediction using statistical characteristics of solar cycles is developed: the solar,cycles are divided into two groups, a high rising velocity (HRV) group and a low rising velocity (LRV) group, depending on the rising velocity in the ascending phase for a given duration of the ascending phase. The amplitude of Solar Cycle 24 can be predicted after the start of the cycle using the formula derived in this paper. Now, about 5 years before the start of the cycle, we can make a preliminary prediction of 83.2-119.4 for its maximum amplitude.

Does a low solar cycle minimum hint at a weak upcoming cycle?

The maximum amplitude （Rm） of a solar cycle, in the term of mean sunspot numbers, is well-known to be positively correlated with the preceding minimum （Rmin）. So far as the long term trend is concerned, a low level of Rmin tends to be followed by a weak Rm, and vice versa. We found that the evidence is insufficient to infer a very weak Cycle 24 from the very low Rmin in the preceding cycle. This is concluded by analyzing the correlation in the temporal variations of parameters for two successive cycles.