Characteristics Of Solar Activity Research Articles

AstroSer: Leveraging Deep Learning for Efficient Content-based Retrieval in Massive Solar-observation Images

Rapid and proficient data retrieval is an essential component of modern astronomical research. In this paper, we address the challenge of retrieving astronomical image content by leveraging state-of-the-art deep learning techniques. We have designed a retrieval model, HybridVR, that integrates the capabilities of the deep learning models ResNet50 and VGG16 and have used it to extract key features of solar activity and solar environmental characteristics from observed images. This model enables efficient image matching and allows for content-based image retrieval (CBIR). Experimental results demonstrate that the model can achieve up to 98% similarity during CBIR while exhibiting adaptability and scalability. Our work has implications for astronomical research, data management, and education, and it can contribute to optimizing the utilization of astronomical image data. It also serves as a useful example of the application of deep learning technology in the field of astronomy.

Spectral Background-subtracted Activity Maps

High-resolution solar spectroscopy provides a wealth of information from photospheric and chromospheric spectral lines. However, the volume of data easily exceeds hundreds of millions of spectra on a single observation day. Therefore, methods are needed to identify spectral signatures of interest in multidimensional data sets. Background-subtracted activity maps (BaSAMs) have previously been used to locate features of solar activity in time series of images and filtergrams. This research note shows how this method can be extended and adapted to spectral data.

Analysis of the Ionospheric Irregularities and Phase Scintillation at Low and Middle Latitudes Based on Swarm Observations

This study presents a statistical analysis of the ionospheric irregularities and topside ionospheric scintillation at low and middle latitudes by using in situ electron density and upward-looking total electron content data measured by the Swarm constellation during 2014–2021. The main purpose of this study is to determine whether the phase scintillation could present similar seasonal, longitudinal, latitudinal, local time, and solar activity features as the in situ ionospheric irregularities do at low and middle latitudes, and how the irregularities affect the phase scintillation. The results are summarized as follows: (1) At low latitudes, the occurrence rate of equatorial plasma irregularities (EPIs) at the equinoxes and December solstice peaks before midnight, but during the June solstice, the EPIs mainly occur after midnight. The occurrence rate of EPIs has a positive correlation with solar activity. The distribution of topside scintillation occurrence is relatively consistent with EPIs, but during the June solstice, the scintillation occurrence rate remains at a very low level. (2) The midlatitude irregularities mainly occur after midnight, and their occurrence rate is negatively correlated with solar activity. Midlatitude irregularities mainly occur during the solstices, concentrated over the Pacific region during the June solstice and over the Pacific American sector during the December solstice. Especially, the distribution of midlatitude irregularities has hemispheric asymmetry, with a higher occurrence rate in the winter hemisphere. However, the occurrence of midlatitude scintillation is comparable in both hemispheres during the June solstice, and it concentrates in the southern hemisphere during the December solstice. (3) The EPIs concentrate more at the altitudes of Swarm A, while the midlatitude irregularities mainly occur at the altitudes of Swarm B.

The Possibility of Observing Several Hydrogen Radio Lines in Solar Activity Features over Sunspots

The Possibility of Observing Several Hydrogen Radio Lines in Solar Activity Features over Sunspots

The Influence of Hemispheric Solar Activity Features on the Interplanetary Plasma Parameters throughout 1967 ̶ 2017

In this article, we have examined the possible influence of hemispheric solar activity features on the interplanetary plasma parameters. For this purpose, the daily data of sunspot areas (SSAs) and sunspot numbers (SSNs) as well as the interplanetary plasma parameters (interplanetary magnetic field (IMF) magnitude B, plasma density n, plasma velocity V, plasma temperature T, and plasma dynamic pressure P) during the period 1967 2017 have been used. The daily data of each interplanetary plasma parameter has been classified into two groups, northern (N) and southern (S) sorted groups based on the dominance of hemispheric SSAs or SSNs. The yearly averages of the sorted N and S groups have been calculated for each plasma parameter. The asymmetry index (N-S) for each parameter between the northern and the southern sorted group has been calculated. The asymmetry of B over the solar activity cycles is not detectable, indicating that the solar cycles are magnetically symmetric, in agreement with the findings of (El-Borie et al., 2018a). During the solar cycles 20, 21, and 24, the solar plasma for the southern sorted group was faster (hotter) by 20.3 km/s (15.7×103 oK), 13 km/s (8×103 oK), and 29 km/s (14.5×103 oK) than that for the northern sorted group, respectively. In contrast, during the solar cycle 23, the solar plasma for the southern sorted group was slower (colder) by 7.4 km/s (7.2×103 oK) than that for the northern sorted one.

The Fine Structure of the Quasi-Biennial Oscillations of Sunspot Areas and the Double Magnetic Cycle of the Sun

One of the basic features of solar activity is the quasi-biennial oscillations (QBOs)—variations with a period of about two years. The nature of the QBO remains unclear and the most puzzling is the high instability of the QBO period. We investigated a fine structure of the QBO period variability as manifested in sunspot area variations in Solar Cycles 19 – 23 using the wavelet transform with a real mother wavelet, Daubechies 10, that provided a high temporal resolution. We found that within every 11-yr solar cycle the QBO period varies not randomly, as it is widely accepted now, but it gradually decreases from the beginning of the solar cycle till the end, in phase with the shift of the average sunspots latitude to the equator. We have analyzed in a similar way the time series which were simulated using a combination of sine waves with different periods (constant and variable one) and red noise with a standard deviation as large as 40% of the sine amplitude. The analysis has shown that noise does not distort significantly the initial signal and noise itself does not form the structures with the properties which were observed in the case of the natural time series. We suppose that the revealed modification of the QBO period with the development of the solar cycle may be related to the latitudinal differential rotation in the solar convection zone and the possible influence of the rotational velocity in the region of the QBO generation on the QBO period value. Under this assumption, the process responsible for the QBO generation should operate in a layer with a substantial latitudinal shear which according to the helioseismology analysis is observed in the bulk of the convection zone and is getting smaller in the vicinity of the tachocline.

SPECTRAL ANALYSIS AND FORECASTING OF THE 25TH SOLAR CYCLES

In the present work, we propose an extrapolation method, developed on the basis of spectral analysis, digital filtering, and the principle of demodulation of a complex signal, for predicting the beginning of cycle 25 of solar activity. The Wolf number and other measured characteristics of solar activity have a very complex spectral composition. The Sun, by the nature of its radiation, contributes a significant stochastic component to the observational data. The experimental data are known only up to the present, and the prediction is about bridging the gap in our data set. Mathematically, the prediction problem boils down to extrapolation of discontinuous functions, which leads to a Gibbs phenomenon that occurs at the point of discontinuity and makes prediction into the future impossible. To overcome this discontinuity, additional physical models describing a continuous process are most often used. This paper uses only the Wolf series of numbers from 1818 to 2020. The authors developed an original forecasting technique using Fourier series, digital filtering and representation of the complex process as modulated and subsequent demodulation. As a result of decomposing the complex signal by Fourier series into separate components, the spectral ranges characteristic of the Wolf number were singled out. Taylor's series was used for construction of prediction or extrapolation algorithms. The extraction of spectral ranges, characteristic for the investigated process, is carried out by means of sequential digital filtering methods and information compression in accordance with the cut-off frequency of the digital filter. For example, when selecting eleven-year cycles of solar activity, we have to compress the information by a factor of 160. With such a processing scheme, the forecasting starts with the ultralow-frequency component with a period of more than 11 years, successively moving to the ranges of higher frequencies. The use of spectral analysis and Chebyshev filtering showed the possibility to predict the low-frequency component for the full cycle period. The eleven-year component forecast obtained by the authors is in good agreement with the data of the Brussels Royal Center.

Variability of Total Column Ozone with Solar Activity Features at Northern and Eastern Regions of India

A statistical study of Total Column Ozone (TCO) with Different solar activity features (DSAF), viz. sunspot number, solar flare, solar active prominences for a Northern station Shimla (31°10'N, 77°17'E) and an Eastern station Imphal (24°82'N, 93°94'E) of India is presented using 11 years (2004-2016) of data. In this study we have compared the trends in TCO with DSAF annually as well as for seasonal months. Our study shows a negative correlation between TCO and DSAF. A negative correlation suggests that there is decrease in Ozone concentration during the given time period with solar activity.

Comparison of automatic methods to detect sunspots in the Coimbra Observatory spectroheliograms

Abstract The Astronomical Observatory of the University of Coimbra has a huge collection of solar images, acquired daily since 1926. From the beginning, only spectroheliograms in the C a ii K line have been recorded, and since 1989 in the H α line also. Such dataset requires efficient tools to detect and analyze solar activity features. The objective of this work is to create a tool that allows to automatically detect sunspots, umbra, and penumbra, that can be applied to the entire dataset. To achieve this, two different approaches have been developed, one based on mathematical morphology and another based on the intensities of the digital levels of the pixels. Both approaches were applied to a subset of images with features identified visually by an experimented solar observer. The performance of both methods was compared through the metrics Precision, Recall and F-score. Another evaluation was made based on the catalogs from Heliophysics Features Catalog and the SILSO catalog.

Reconstruction of the coupling between solar proxies: When approaches based on Kuramoto and Van der Pol models agree with each other

The objective of this paper is to establish that algorithms, which reconstruct the coupling between solar proxies based on the properties of the Kuramoto equations, and algorithms, based on the van der Pol equations, might produce similar estimates. To this end, the inverse problem is formulated as follows: reconstruct the coupling based on the solutions of the corresponding equations. For either system of the equations we construct an algorithm solving the inverse problem and establish that there exists a range of moderate values of the correlation such that the algorithms produce practically identical coupling within the established range. The lower boundary of this range is dependent on the half-difference of the oscillators’ frequencies. Then, we apply the two reconstruction algorithms to solar index ISSN and the geomagnetic index aa, which are proxies to the toroidal and poloidal magnetic fields of the Sun respectively. Their correlation belongs within the range that yields the proximity of the coupling reconstructed with all solar cycles from 11 till 23 except 20 and, possibly, 21. Our finding relate the reconstruction of characteristics of solar activity inferred by Blanter et al [Sol. Phys. 2014, 289, 4309; Sol. Phys. 2016, 291, 1003] from the Kuramoto model to the state of the art solar dynamo theory based on the magnetohydrodynamic equations.

Space weather and hurricanes Irma, Jose and Katia

This research is devoted to the determination of the causal relationship between the flow of particles that are coming from the Sun and the hurricanes Irma, Jose, and Katia. To accomplish this, the lag correlation analysis was performed. High correlation coefficients confirmed a preliminary conclusion about the relationship between solar activities and the hurricane phenomenon, which allows further research. Five parameters i.e. characteristics of solar activity (10.7 cm solar radio flux (F10.7), the flows of protons and electrons with maximum energy, speed and density of solar wind particles) were chosen as model input, while the wind speed and air pressure of Irma, Jose, and Katia hurricanes were used as model output. Input data were sampled to a six hours interval in order to adapt the time interval to the observed data about hurricanes, in the period between September 28 and December 21, 2017. As a result of the preliminary analysis, using 12,274,264 linear models by parallel calculations, six of them were chosen as best. The identified lags were the basis for refinement of models with the artificial neural networks. Multilayer perceptrons with back propagation and recurrent LSTM have been chosen as commonly used artificial neural networks. Comparison of the accuracy of both linear and artificial neural networks results confirmed the adequacy of these models and made it possible to take into account the dynamics of the solar wind. Sensitivity analysis has shown that F10.7 has the greatest impact on the wind speed of the hurricanes. Despite low sensitivity of pressure to change the parameters of the solar wind, their strong fluctuations can cause a sharp decrease in pressure, and therefore the appearance of hurricanes.

Application of Soft Computing (ANN) Techniques to study the relationship between Solar Activity Features and Total Column Ozone

Using 30 years data (1986-2015) we have made an attempt to study the dependency of total column ozone (TCO) on solar activity features: solar flares (SF), solar active prominence (SAP) and sunspot numbers (SN) for two hill stations of Uttarakhand viz. Nainital (29.40 N.79.470E) and Mussorie (30.270 N 78.060 E) by Artificial neural network (ANN) technique. Our study supports the fact that solar activity features contribute to the production of ozone

Dependence of Rainfall on Solar Activity Features

In the present paper, we have studied the statistical analysis between all India homogeneous rainfall (RF) with sunspot number (SN) during 1900-2014 (115-year period). We have calculated correlations coefficient of rainfall with sunspot number (SN) for annual and seasonal months: January, February (JF); March April May (MAM); June July August September (JJAS) and October November December (OND) and we have obtained high correlation ranging between 0.75 to 0.95. Our results show that rainfall is strongly influenced by sunspot number. Our study also indicates that occurrence of solar activity features play an important role for variability of rainfall.

Dependence of Rainfall on Solar Activity Features

In the present paper, we have studied the statistical analysis between all India homogeneous rainfall (RF) with sunspot number (SN) during 1900-2014 (115-year period). We have calculated correlations coefficient of rainfall with sunspot number (SN) for annual and seasonal months: January, February (JF); March April May (MAM); June July August September (JJAS) and October November December (OND) and we have obtained high correlation ranging between 0.75 to 0.95. Our results show that rainfall is strongly influenced by sunspot number. Our study also indicates that occurrence of solar activity features play an important role for variability of rainfall.

Application of Soft Computing (ANN) Techniques to study the relationship between Solar Activity Features and Total Column Ozone

Using 30 years data (1986-2015) we have made an attempt to study the dependency of total column ozone (TCO) on solar activity features: solar flares (SF), solar active prominence (SAP) and sunspot numbers (SN) for two hill stations of Uttarakhand viz. Nainital (29.40 N.79.470E) and Mussorie (30.270 N 78.060 E) by Artificial neural network (ANN) technique. Our study supports the fact that solar activity features contribute to the production of ozone.

Analysis of sea level changes in the Caspian Sea related to Cosmo-geophysical processes based on satellite and terrestrial data

Analysis results of the average annual sea levels in the Caspian Sea obtained from ground and satellite observations, corresponding to solar activity characteristics, magnetic field data, and length of day are presented. Spectra of the indicated processes were investigated and their approximation models were also built. Previously assumed statistical relationships between space-geophysical processes and Caspian Sea level (CSL) changes were confirmed. A close connection was revealed between the low-frequency models of the solar and geomagnetic activity parameters and the CSL changes. Predictions extending into the next decades showed a high probability of an increase in the CSL and a decrease of the compared space-geophysical parameters.

Software tool for automatic detection of solar plages in the Coimbra Observatory spectroheliograms

Full-disk spectroheliograms have been taken in Coimbra on a daily basis since 1926 in the Ca II K-line (K1 and K3). Later, in 1989, with the upgrade of the equipment it was possible to start the observations in the H-alpha line. The spectroheliograms of Coimbra constitutes a huge dataset of solar images, which requires an efficient automatic tool to detect and analyse solar activity features. This work presents a mathematical morphology approach applied to the CaII K3 series. The objective is to create a tool based on the segmentation by watershed transform combined with other morphological operators to detect automatically and analyse chromospheric plages during the solar cycle 24. The tool is validated by comparing its results for cycle 23 with those presented by Dorotovic et al. (2007, 2010). The results obtained are in very good agreement with those, including on images obtained in non-ideal meteorological conditions (eg. some clouds in sky). The results were also qualitatively compared with the results obtained through the application of ASSA model to SDO HMI magnetograms.

A study of the asymmetrical distribution of solar activity features on solar and plasma parameters (1967–2016)

The impact of asymmetrical distribution of hemispheric sunspot areas (SSAs) on the interplanetary magnetic field, plasma, and solar parameters from 1967 to 2016 has been studied. The N-S asymmetry of solar-plasma activities based on SSAs has a northern dominance during solar cycles 20 and 24. However, it has a tendency to shift to the southern hemisphere in cycles 21, 22, and 23. The solar cycle 23 showed that the sorted southern SSAs days predominated over the northern days by ∼17%. Through the solar cycles 21–24, the SSAs of the southern hemisphere were more active. In contrast, the northern SSAs predominate over the southern one by 9% throughout solar cycle 20. On the other hand, the average differences of field magnitude for the sorted northern and southern groups during solar cycles 20–24 are statistically insignificant. Clearly, twenty years showed that the solar plasma ion density from the sorted northern group was denser than that of southern group and a highest northern dominant peak occurred in 1971. In contrast, seventeen out of fifty years showed the reverse. In addition, there are fifteen clear asymmetries of solar wind speed (SWS), with SWS (N) > SWS (S), and during the years 1972, 2002, and 2008, the SWS from the sorted northern group was faster than that of southern activity group by 6.16 ± 0.65 km/s, 5.70 ± 0.86 km/s, and 5.76 ± 1.35 km/s, respectively. For the solar cycles 20–24, the grand-averages of P from the sorted solar northern and southern have nearly the same parameter values. The solar plasma was hotter for the sorted northern activity group than the southern ones for 17 years out of 50. Most significant northern prevalent asymmetries were found in 1972 (5.76 ± 0.66 × 103 K) and 1996 (4.7 ± 0.8 × 103 K), while two significant equivalent dominant southern asymmetries (∼3.8 ± 0.3 × 103 K) occurred in 1978 and 1993. The grand averages of sunspot numbers have symmetric activity for the two sorted northern and southern hemispheres through the solar cycles 20 and 21. The sunspots tend to be the southern dominance during the solar cycles 22 and 23, and it shifted during solar cycle 24 to symmetric distribution on both solar hemispheres.

Century long study of sunspot activity using the Kodaikanal white-light data

AbstractSunspots are the most obvious and high contrast observable feature of solar magnetic activity in the photosphere. The morphological and kinematic behavior of sunspots on the solar surface need to be studied over a long time period to understand solar magnetic activity. For this, it is important to understand the long term emergence patterns, and developments, decay of the sunspots on the solar surface over many cycles. The long time sequence of the Kodaikanal white-light images provide a consistent data set for this study. The digitized images were calibrated for relative plate density and aligned in such a way that the solar north is in upward direction. A sunspot detection technique was used to identify the sunspots on the digitized images. In addition to describing the calibration procedure and availability of the data, we here present results on the sunspot, umbral and penumbral area measurements and their variation with time.

Halo coronal mass ejections during Solar Cycle 24: reconstruction of the global scenario and geoeffectiveness

Coronal mass ejections (CMEs), in particular Earth-directed ones, are regarded as the main drivers of geomagnetic activity. In this study, we present a statistical analysis of a set of 53 fast (V ≥ 1000 km·s−1) Earth-directed halo CMEs observed by the SOHO/LASCO instrument during the period Jan. 2009–Sep. 2015, and we then use this CME sample to test the forecasting capabilities of a new Sun-to-Earth prediction scheme for the geoeffectiveness of Earth-directed halo CMEs. First, we investigate the CME association with other solar activity features such as solar flares, active regions, and others, by means of multi-instrument observations of the solar magnetic and plasma properties, with the final aim of identifying recurrent peculiar features that can be used as precursors of CME-driven geomagnetic storms. Second, using coronagraphic images to derive the CME kinematical properties at 0.1 AU, we propagate the events to 1 AU by means of 3D global MHD simulations. In particular, we use the WSA-ENLIL+Cone model to reconstruct the propagation and global evolution of each event up to their arrival at Earth, where simulation results are compared with interplanetary CME (ICME) in-situ signatures. We then use simulation outputs upstream of Earth to predict their impact on geospace. By applying the pressure balance condition at the magnetopause and the coupling function proposed by Newell et al. [J Geophys Res: Space Phys 113 (2008)] to link upstream solar wind properties to the global Kp index, we estimate the expected magnetospheric compression and geomagnetic activity level, and compare our predictions with global data records. The analysis indicates that 82% of the fast Earth-directed halo CMEs arrived at Earth within the next 4 days. Almost the totality of them compressed the magnetopause below geosynchronous orbits and triggered a minor or major geomagnetic storm afterwards. Among them, complex sunspot-rich active regions associated with X- and M-class flares are the most favourable configurations from which geoeffective CMEs originate. The analysis of related Solar Energetic Particle (SEP) events shows that 74% of the CMEs associated with major SEPs were geoeffective, i.e. they triggered a minor to intense geomagnetic storm (Kp ≥ 5). Moreover, the SEP production is enhanced in the case of fast and interacting CMEs. In this work we present a first attempt at applying a Sun-to-Earth geoeffectiveness prediction scheme − based on 3D simulations and solar wind-geomagnetic activity coupling functions − to a statistical set of fast Earth-directed, potentially geoeffective halo CMEs. The results of the prediction scheme are promising and in good agreement with the actual data records for geomagnetic activity. However, we point out the need for future studies performing a fine-tuning of the prediction scheme, in particular in terms of the evaluation of the CME input parameters and the modelling of their internal magnetic structure.