This study analyzes the evolution and dynamics of intensity oscillations in coronal sunspots and their surroundings using multi-wavelength image data from the Atmospheric Imaging Assembly(AIA)and Helioseismic and Magn...This study analyzes the evolution and dynamics of intensity oscillations in coronal sunspots and their surroundings using multi-wavelength image data from the Atmospheric Imaging Assembly(AIA)and Helioseismic and Magnetic Imager(HMI)on board the Solar Dynamics Observatory(SDO).Intensity time series were extracted and analyzed from consecutive macropixels along thin coronal loop paths originating in a quiet sunspot.Fourier and wavelet analyses of corrected intensity time series reveal dominant 3 and 5 minute oscillations.Signals were filtered using the Fourier and inverse transforms to isolate narrow bands around the dominant oscillation periods.Diagrams and time-distance maps of intensity time series were plotted for Fourierfiltered AIA 131A,171A,193A,and 211A channels,along with SDO/HMI magnetograms and dopplergrams at 6173A.The plots clearly show propagating oscillations with amplitude modulation(AM)across all macropixels along selected coronal paths in nearly all AIA and HMI channels.The phase speeds of the filtered oscillations,measured via slope calculations in time-distance maps,indicate that the intensity disturbances are slow magneto-acoustic waves.These results suggest that AM likely arises from the superposition of counterpropagating waves with slightly different frequencies(beta-like phenomena)due to Doppler shifts from background plasma flow along loop paths.Validating this hypothesis could establish AM's significance in solar coronal seismology for determining background plasma flow speed,the source of long-period oscillations,and coronal plasma heating mechanisms.展开更多
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 ap...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.展开更多
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 tempe...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.展开更多
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 choi...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.展开更多
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...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.展开更多
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), time...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.展开更多
We examined the heliolatitude distribution and North-South(N-S)asymmetry of Ground Level Enhancement(GLE)event source locations from 1942 to 2024,finding distinct patterns between the periods 1942–1979 and1980–2024....We examined the heliolatitude distribution and North-South(N-S)asymmetry of Ground Level Enhancement(GLE)event source locations from 1942 to 2024,finding distinct patterns between the periods 1942–1979 and1980–2024.Between 1942 and 1979,33 GLE events were recorded:5 from the southern hemisphere within[S3,S11]and 28 from the northern hemisphere within[N7,N37].The southeast quadrant was devoid of any source locations for GLE events.45.4%of the source locations of the GLE events were within the latitudinal range of[S15,N15].The remaining source locations of the GLE events were distributed at latitudes above 15°in the northern hemisphere.Between 1980 and 2024,43 GLE events were recorded:25 from the southern hemisphere and 18 from the northern hemisphere,with all events above 30°latitude originating from the northern hemisphere.Approximately 44.2%of the source locations of the GLE events were distributed within the latitudinal band[S15,N15].Over the period from 1942 to 2024,44.7%within[S15,N15],63.2%within[S20,N20],80.3%within[S25,N25],88.2%within[S30,N30],and 11.8%at latitudes above 30°.N-S asymmetry was significant at latitudes above 0°,5°,10°,15°,20°and 30°,with northern hemisphere dominance.Moreover,a strong inverse correlation exists between the number of GLE events from the northern and southern hemispheres at latitudes above 0°,5°,10°,15°,20°,25°and 30°.展开更多
The Gnevyshev-Ohl(G-O)rule,or even-odd effect,is an important observational phenomenon in solar cycles,originally suggesting that even-numbered cycles are typically followed by stronger odd-numbered ones.However,subse...The Gnevyshev-Ohl(G-O)rule,or even-odd effect,is an important observational phenomenon in solar cycles,originally suggesting that even-numbered cycles are typically followed by stronger odd-numbered ones.However,subsequent studies have reported varied forms and often conflicting manifestations of this rule,along with diverse interpretations of its physical origin.Using an observation-based iterative map,we investigate these different forms of the G-O rule and propose a more general underlying rule:statistically,a given solar cycle is more likely to be followed by a stronger one,regardless of even-odd numbering.This transition asymmetry arises from the map's inherent asymmetry relative to the diagonal.Over timescales comparable to historical observations,both the G-O rule and its reversal can arise randomly,without a consistent preference.The short-term behavior of the rule is sensitive to the initial cycle,the selected time interval,and the parameters of the recursion function.These findings reconcile previously conflicting reports and point to a general generation mechanism:G-O-like behavior arises naturally from nonlinear stochastic dynamics.While different recursion parameters may lead to varying short-term patterns and statistical strengths,the emergence of G-O-like features appears to be a generic property of such systems.展开更多
With the advancement of astronomical observation technology,people have a deeper understanding of the formation and evolution of galaxies,but many details of our own Milky Way and other external galaxies are still unk...With the advancement of astronomical observation technology,people have a deeper understanding of the formation and evolution of galaxies,but many details of our own Milky Way and other external galaxies are still unknown.Therefore,by studying the formation and orbital transformation mechanism of satellites,planets and stars,the author puts forward a new theory on the formation and evolution of stars and galaxies,thus revealing the hierarchical structure of galaxies and the formation and evolution laws of main sequence stars,red giants,white dwarfs,black dwarfs,supernovae,neutron stars,black holes and quasars.Some special phenomena in the course of star formation and evolution,such as sunspots,flares,fast radio bursts and gamma-ray bursts,have also been revealed.展开更多
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 var...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.展开更多
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 monthl...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.展开更多
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 ope...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.展开更多
Predicting the activity of solar flares is of great significance for studying its physical mechanism and the impact on human production and life.Problems such as class imbalance,high time-series sensitivity,and over-l...Predicting the activity of solar flares is of great significance for studying its physical mechanism and the impact on human production and life.Problems such as class imbalance,high time-series sensitivity,and over-localization of important features exist in the sample data used for flare forecasting.We design a solar flare fusion method based on resampling and the CNN-GRU algorithm to try to solve the above problems.In order to verify the effectiveness of this fusion method,first,we compared the forecast performance of different resampling methods by keeping the forecast model unchanged.Then,we used the resampling algorithm with high performance to combine some single forecast models and fusion forecast models respectively.We use the 2010-2017 sunspot data set to train and test the performance of the flare model in predicting flare events in the next 48 h.Through the conclusion of the above steps,we prove that the resampling method SMOTE and its variant SMOTE-ENN are more advantageous in class imbalance problem of flare samples.In addition,after the fusion of one-dimensional convolution and recurrent network with"forget-gate",combined with the SMOTE-ENN to achieve TSS=61%,HSS=61%,TP_(Rate)=77%and TN_(Rate)=83%.This proves that the fusion model based on resampling and the CNN-GRU algorithm is more suitable for solar flare forecasting.展开更多
Using data-driven algorithms to accurately forecast solar flares requires reliable data sets.The solar flare dataset is composed of many non-flaring samples with a small percentage of flaring samples.This is called th...Using data-driven algorithms to accurately forecast solar flares requires reliable data sets.The solar flare dataset is composed of many non-flaring samples with a small percentage of flaring samples.This is called the class imbalance problem in data mining tasks.The prediction model is sensitive to most classes of the original data set during training.Therefore,the class imbalance problem for building up the flare prediction model from observational data should be systematically discussed.Aiming at the problem of class imbalance,three strategies are proposed corresponding to the data set,loss function,and training process:TypeⅠresamples the training samples,including oversampling for the minority class,undersampling,or mixed sampling for the majority class.TypeⅡusually changes the decision-making boundary,assigning the majority and minority categories of prediction loss to different weights.TypeⅢassigns different weights to the training samples,the majority categories are assigned smaller weights,and the minority categories are assigned larger weights to improve the training process of the prediction model.The main work of this paper compares these imbalance processing methods when building a flare prediction model and tries to find the optimal strategy.Our results show that among these strategies,the performance of oversampling and sample weighting is better than other strategies in most parameters,and the generality of resampling and changing the decision boundary is better.展开更多
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 leve...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.展开更多
Using multi-wavelength data of Hinode, the rapid rotation of a sunspot in active region NOAA 10930 is studied in detail. We found extraordinary counterclockwise rotation of the sunspot with positive polarity before an...Using multi-wavelength data of Hinode, the rapid rotation of a sunspot in active region NOAA 10930 is studied in detail. We found extraordinary counterclockwise rotation of the sunspot with positive polarity before an X3.4 flare. From a series of vector magnetograms, it is found that magnetic force lines are highly sheared along the neutral line accompanying the sunspot rotation. Furthermore, it is also found that sheared loops and an inverse S-shaped magnetic loop in the corona formed gradually after the sunspot rotation. The X3.4 flare can be reasonably regarded as a result of this movement. A detailed analysis provides evidence that sunspot rotation leads to magnetic field lines twisting in the photosphere. The twist is then transported into the corona and triggers flares.展开更多
We examine the solar cycle distribution of major geomagnetic storms （Dst ≤ -100 nT）, including intense storms at the level of -200 nT〈 Dst ≤ -100 nT, great storms at -300 nT〈 Dst ≤-200 nT, and super storms at D...We examine the solar cycle distribution of major geomagnetic storms （Dst ≤ -100 nT）, including intense storms at the level of -200 nT〈 Dst ≤ -100 nT, great storms at -300 nT〈 Dst ≤-200 nT, and super storms at Dst ≤ -300 nT, which occurred during the period of 1957-2006, based on Dst indices and smoothed monthly sunspot numbers. Statistics show that the majority （82%） of the geomagnetic storms at the level of Dst≤ -100 nT that occurred in the study pe- riod were intense geomagnetic storms, with 12.4% ranked as great storms and 5.6% as super storms. It is interesting to note that about 27% of the geomagnetic storms that occurred at all three intensity levels appeared in the ascending phase of a solar cycle, and about 73% in the descending one. Statistics also show that 76.9% of the intense storms, 79.6% of the great storms and 90.9% of the super storms occurred during the two years before a solar cycle reached its peak, or in the three years after it. The correlation between the size of a solar cycle and the percentage of major storms that occurred, during the period from two years prior to maximum to three years af- ter it, is investigated. Finally, the properties of the multi-peak distribution for major geomagnetic storms in each solar cycle is investigated.展开更多
We investigate the wavelet transform of yearly mean relative sunspot number series from 1700 to 2002. The curve of the global wavelet power spectrum peaks at 11-yr, 53-yr and 101-yr periods. The evolution of the ampli...We investigate the wavelet transform of yearly mean relative sunspot number series from 1700 to 2002. The curve of the global wavelet power spectrum peaks at 11-yr, 53-yr and 101-yr periods. The evolution of the amplitudes of the three periods is studied. The results show that around 1750 and 1800, the amplitude of the 53-yr period was much higher than that of the the 11-yr period, that the ca. 53-yr period was apparent only for the interval from 1725 to 1850, and was very low after 1850, that around 1750, 1800 and 1900, the amplitude of the 101-yr period was higher than that of the 11-yr period and that, from 1940 to 2000, the 11-yr period greatly dominates over the other two periods.展开更多
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...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.展开更多
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 n...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.展开更多
文摘This study analyzes the evolution and dynamics of intensity oscillations in coronal sunspots and their surroundings using multi-wavelength image data from the Atmospheric Imaging Assembly(AIA)and Helioseismic and Magnetic Imager(HMI)on board the Solar Dynamics Observatory(SDO).Intensity time series were extracted and analyzed from consecutive macropixels along thin coronal loop paths originating in a quiet sunspot.Fourier and wavelet analyses of corrected intensity time series reveal dominant 3 and 5 minute oscillations.Signals were filtered using the Fourier and inverse transforms to isolate narrow bands around the dominant oscillation periods.Diagrams and time-distance maps of intensity time series were plotted for Fourierfiltered AIA 131A,171A,193A,and 211A channels,along with SDO/HMI magnetograms and dopplergrams at 6173A.The plots clearly show propagating oscillations with amplitude modulation(AM)across all macropixels along selected coronal paths in nearly all AIA and HMI channels.The phase speeds of the filtered oscillations,measured via slope calculations in time-distance maps,indicate that the intensity disturbances are slow magneto-acoustic waves.These results suggest that AM likely arises from the superposition of counterpropagating waves with slightly different frequencies(beta-like phenomena)due to Doppler shifts from background plasma flow along loop paths.Validating this hypothesis could establish AM's significance in solar coronal seismology for determining background plasma flow speed,the source of long-period oscillations,and coronal plasma heating mechanisms.
文摘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.
文摘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.
文摘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.
基金supported by the National Natural Science Foundation of China(11573065 and 11633008)the Specialized Research Fund for State Key Laboratories and the Chinese Academy of Sciences
文摘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.
文摘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.
基金supported by the National Natural Science Foundation of China(grant Nos.42374092,41074132,41274193,41474166,41774195,and 41874187)the Special Fund of the Institute of Geophysics,China Earthquake Administration(Grant Number DQJB22X12)。
文摘We examined the heliolatitude distribution and North-South(N-S)asymmetry of Ground Level Enhancement(GLE)event source locations from 1942 to 2024,finding distinct patterns between the periods 1942–1979 and1980–2024.Between 1942 and 1979,33 GLE events were recorded:5 from the southern hemisphere within[S3,S11]and 28 from the northern hemisphere within[N7,N37].The southeast quadrant was devoid of any source locations for GLE events.45.4%of the source locations of the GLE events were within the latitudinal range of[S15,N15].The remaining source locations of the GLE events were distributed at latitudes above 15°in the northern hemisphere.Between 1980 and 2024,43 GLE events were recorded:25 from the southern hemisphere and 18 from the northern hemisphere,with all events above 30°latitude originating from the northern hemisphere.Approximately 44.2%of the source locations of the GLE events were distributed within the latitudinal band[S15,N15].Over the period from 1942 to 2024,44.7%within[S15,N15],63.2%within[S20,N20],80.3%within[S25,N25],88.2%within[S30,N30],and 11.8%at latitudes above 30°.N-S asymmetry was significant at latitudes above 0°,5°,10°,15°,20°and 30°,with northern hemisphere dominance.Moreover,a strong inverse correlation exists between the number of GLE events from the northern and southern hemispheres at latitudes above 0°,5°,10°,15°,20°,25°and 30°.
基金supported by the National Key R&D Program of China through grant No.2022YFF0503800the Strategic Priority Program of Chinese Academy of Sciences through grant No.XDB0560000+2 种基金the State Key Program of National Natural Science of China(grant No.12533010)the National Natural Science Foundation of China(grant Nos.12503062,12350004,12273061,12373111,&12403067)the Specialized Research Fund for State Key Laboratory of Solar Activity and Space Weather。
文摘The Gnevyshev-Ohl(G-O)rule,or even-odd effect,is an important observational phenomenon in solar cycles,originally suggesting that even-numbered cycles are typically followed by stronger odd-numbered ones.However,subsequent studies have reported varied forms and often conflicting manifestations of this rule,along with diverse interpretations of its physical origin.Using an observation-based iterative map,we investigate these different forms of the G-O rule and propose a more general underlying rule:statistically,a given solar cycle is more likely to be followed by a stronger one,regardless of even-odd numbering.This transition asymmetry arises from the map's inherent asymmetry relative to the diagonal.Over timescales comparable to historical observations,both the G-O rule and its reversal can arise randomly,without a consistent preference.The short-term behavior of the rule is sensitive to the initial cycle,the selected time interval,and the parameters of the recursion function.These findings reconcile previously conflicting reports and point to a general generation mechanism:G-O-like behavior arises naturally from nonlinear stochastic dynamics.While different recursion parameters may lead to varying short-term patterns and statistical strengths,the emergence of G-O-like features appears to be a generic property of such systems.
文摘With the advancement of astronomical observation technology,people have a deeper understanding of the formation and evolution of galaxies,but many details of our own Milky Way and other external galaxies are still unknown.Therefore,by studying the formation and orbital transformation mechanism of satellites,planets and stars,the author puts forward a new theory on the formation and evolution of stars and galaxies,thus revealing the hierarchical structure of galaxies and the formation and evolution laws of main sequence stars,red giants,white dwarfs,black dwarfs,supernovae,neutron stars,black holes and quasars.Some special phenomena in the course of star formation and evolution,such as sunspots,flares,fast radio bursts and gamma-ray bursts,have also been revealed.
基金Supported by the National Natural Science Foundation of China
文摘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.
基金the Chinese Academy of Sciences through Grant KGCX3-SYW-403-10the NSFC through Grants 10733020 and 10673017the National Ministry of Science and Technology through Grant 2006CB806307
文摘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.
基金This work is supported by National Nature Science Foundation Project No.4999-0451Space Environmental Prediction CenterCenter for Space Science and Applied Research, CAS, China.
文摘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.
基金the National Natural Science Foundation of China(Grant No.11975086)project“3D Magnetic Reconnection Reconnection Area Structure Experimental and Numerical Simulation Research”。
文摘Predicting the activity of solar flares is of great significance for studying its physical mechanism and the impact on human production and life.Problems such as class imbalance,high time-series sensitivity,and over-localization of important features exist in the sample data used for flare forecasting.We design a solar flare fusion method based on resampling and the CNN-GRU algorithm to try to solve the above problems.In order to verify the effectiveness of this fusion method,first,we compared the forecast performance of different resampling methods by keeping the forecast model unchanged.Then,we used the resampling algorithm with high performance to combine some single forecast models and fusion forecast models respectively.We use the 2010-2017 sunspot data set to train and test the performance of the flare model in predicting flare events in the next 48 h.Through the conclusion of the above steps,we prove that the resampling method SMOTE and its variant SMOTE-ENN are more advantageous in class imbalance problem of flare samples.In addition,after the fusion of one-dimensional convolution and recurrent network with"forget-gate",combined with the SMOTE-ENN to achieve TSS=61%,HSS=61%,TP_(Rate)=77%and TN_(Rate)=83%.This proves that the fusion model based on resampling and the CNN-GRU algorithm is more suitable for solar flare forecasting.
文摘Using data-driven algorithms to accurately forecast solar flares requires reliable data sets.The solar flare dataset is composed of many non-flaring samples with a small percentage of flaring samples.This is called the class imbalance problem in data mining tasks.The prediction model is sensitive to most classes of the original data set during training.Therefore,the class imbalance problem for building up the flare prediction model from observational data should be systematically discussed.Aiming at the problem of class imbalance,three strategies are proposed corresponding to the data set,loss function,and training process:TypeⅠresamples the training samples,including oversampling for the minority class,undersampling,or mixed sampling for the majority class.TypeⅡusually changes the decision-making boundary,assigning the majority and minority categories of prediction loss to different weights.TypeⅢassigns different weights to the training samples,the majority categories are assigned smaller weights,and the minority categories are assigned larger weights to improve the training process of the prediction model.The main work of this paper compares these imbalance processing methods when building a flare prediction model and tries to find the optimal strategy.Our results show that among these strategies,the performance of oversampling and sample weighting is better than other strategies in most parameters,and the generality of resampling and changing the decision boundary is better.
基金Supported by the National Natural Science Foundation of China(Grant Nos.10973020 and 40890161)supported by the Chinese Academy of Sciences through grant KJCX2-YWT04
文摘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.
基金supported by the National Science Foundation of China (NSFC) undergrant numbers 10673031 and 40636031the National Basic Research Program of China 973 undergrant number G2006CB806301.
文摘Using multi-wavelength data of Hinode, the rapid rotation of a sunspot in active region NOAA 10930 is studied in detail. We found extraordinary counterclockwise rotation of the sunspot with positive polarity before an X3.4 flare. From a series of vector magnetograms, it is found that magnetic force lines are highly sheared along the neutral line accompanying the sunspot rotation. Furthermore, it is also found that sheared loops and an inverse S-shaped magnetic loop in the corona formed gradually after the sunspot rotation. The X3.4 flare can be reasonably regarded as a result of this movement. A detailed analysis provides evidence that sunspot rotation leads to magnetic field lines twisting in the photosphere. The twist is then transported into the corona and triggers flares.
基金supported by the National Basic Research Program of China (973 Program, Grant Nos. 2012CB957801 and 2011CB811406)the National Natural Science Foundation of China (Grant Nos. 41074132, 41274193 and 40931056)the National Standard Research Program (Grant No. 10-123)
文摘We examine the solar cycle distribution of major geomagnetic storms （Dst ≤ -100 nT）, including intense storms at the level of -200 nT〈 Dst ≤ -100 nT, great storms at -300 nT〈 Dst ≤-200 nT, and super storms at Dst ≤ -300 nT, which occurred during the period of 1957-2006, based on Dst indices and smoothed monthly sunspot numbers. Statistics show that the majority （82%） of the geomagnetic storms at the level of Dst≤ -100 nT that occurred in the study pe- riod were intense geomagnetic storms, with 12.4% ranked as great storms and 5.6% as super storms. It is interesting to note that about 27% of the geomagnetic storms that occurred at all three intensity levels appeared in the ascending phase of a solar cycle, and about 73% in the descending one. Statistics also show that 76.9% of the intense storms, 79.6% of the great storms and 90.9% of the super storms occurred during the two years before a solar cycle reached its peak, or in the three years after it. The correlation between the size of a solar cycle and the percentage of major storms that occurred, during the period from two years prior to maximum to three years af- ter it, is investigated. Finally, the properties of the multi-peak distribution for major geomagnetic storms in each solar cycle is investigated.
基金Supported by the National Natural Science Foundation of China
文摘We investigate the wavelet transform of yearly mean relative sunspot number series from 1700 to 2002. The curve of the global wavelet power spectrum peaks at 11-yr, 53-yr and 101-yr periods. The evolution of the amplitudes of the three periods is studied. The results show that around 1750 and 1800, the amplitude of the 53-yr period was much higher than that of the the 11-yr period, that the ca. 53-yr period was apparent only for the interval from 1725 to 1850, and was very low after 1850, that around 1750, 1800 and 1900, the amplitude of the 101-yr period was higher than that of the 11-yr period and that, from 1940 to 2000, the 11-yr period greatly dominates over the other two periods.
基金the support of the National Key Research and Development Program of China(No.2022YFF0503601)the National Natural Science Foundation of China(No.11975086)。
文摘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.
基金the support of the National Key Research and Development Program of China(No.2022YFA1604600)the National Natural Science Foundation of China(NSFC,Grant No.11975086)。
文摘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.
