Solar Activity Indices Research Articles

Circulatory and Nervous Diseases Mortality Patterns—Comparison of Geomagnetic Storms and Quiet Periods

The aim of this paper is to statistically examine whether there are different patterns in daily numbers of deaths during the quiet periods of solar activity, in contrast to the periods of the strong solar storms. We considered three periods of solar storms (storm of 14 July 2000 Bastille Day Event, storm of 28 October 2003 Halloween Solar Storms, and storm of 17 March 2015 St. Patrick’s Day event) and three periods of continuous very low solar activity (13 September–24 October 1996, 21 July–20 August 2008, and 31 July–31 August 2009) during the Solar Cycles No. 23 and No. 24. In particular, we focus on diseases of the nervous system (group VI from ICD-10) and diseases of the circulatory system (group IX from ICD-10) separately for both sexes and two age groups (under 39 and 40+). We demonstrate that in the resulting graphical models there was a connection between the daily number of deaths and all indices of solar and geomagnetic activity in periods of low solar activity in contrast to periods of strong solar storms in some monitored groups according to age, sex, and group of diagnosis.

Solar-Activity Indices for the Ionosphere in Cycles 23 and 24: the Form of Cycles

Solar-Activity Indices for the Ionosphere in Cycles 23 and 24: the Form of Cycles

RMCSat: An F10.7 Solar Flux Index CubeSat Mission

The F10.7 solar flux index is a measure of microwave solar emissions at a wavelength of 10.7 cm or 2800 MHz. It is widely used in thermosphere and ionosphere models as an indicator of solar activity and is recorded at only one terrestrial observatory in Penticton, Canada during daylight hours. The lack of geographical and temporal coverage of F10.7 measurements and no external redundancy to the existing system has led to the development of the RMCSat mission, which seeks to demonstrate the feasibility of collecting microwave solar flux emissions from a space-based platform. RMCSat is the first CubeSat mission by the Royal Military College of Canada. It offers a training environment for personnel in space mission analysis and design, satellite assembly, integration and testing, and satellite operations. This paper introduces the mission concept and preliminary design of a space-based solution that captures solar density flux measurements during each orbit as the Sun passes through the boresight of the primary payload antenna. In addition to two channels recording the 2800 MHz frequency (2785 MHz and 2815 MHz), a third channel records 2695 MHz using the same calibration standard to determine if the United States Radio Solar Telescope Network (RSTN) could be leveraged to supplement the existing F10.7 solar flux measurements and improve solar flux approximations. The RMCSat mission, satellite design, and system budgets are demonstrated here as being viable. Future design considerations pertain to the payload antennas and achievable launch orbits.

Prediction of Sunspot and Plage Coverage for Solar Cycle 25

Abstract Solar variability occurs over a broad range of spatial and temporal scales, from the Sun’s brightening over its lifetime to the fluctuations commonly associated with magnetic activity over minutes to years. The latter activity includes most prominently the 11 yr sunspot solar cycle and its modulations. Space weather events, in the form of solar flares, solar energetic particles, coronal mass ejections, and geomagnetic storms, have long been known to approximately follow the solar cycle occurring more frequently at solar maximum than solar minimum. These events can significantly impact our advanced technologies and critical infrastructures, making the prediction for the strength of future solar cycles particularly important. Several methods have been proposed to predict the strength of the next solar cycle, cycle 25, with results that are generally not always consistent. Most of these methods are based on the international sunspot number time series, or other indicators of solar activity. We present here a new approach that uses more than 100 yr of measured fractional areas of the visible solar disk covered by sunspots and plages and an empirical relationship for each of these two indices of solar activity in even–odd cycles. We anticipate that cycle 25 will peak in 2024 and will last for about 12 yr, slightly longer than cycle 24. We also found that, in terms of sunspot and plage areas coverage, the amplitude of cycle 25 will be substantially similar or slightly higher than cycle 24.

Relation of the Monthly Mean Ionospheric T Index to Solar and Geomagnetic Activity Indices

Relation of the Monthly Mean Ionospheric T Index to Solar and Geomagnetic Activity Indices

Evaluation of the 900‐Year European Auroral Records With Extreme Value Theory

AbstractAn explicit proxy of solar activity on the Earth is the auroral displays. The auroral oval can extend to lower latitudes during geomagnetic storms triggered by explosive solar activities. The lower the latitude of auroral oval is, the stronger the solar activity is. Systematic auroral records in Europe (mainly central Europe with geomagnetic latitude lower than 55°) can be dated back to 1000 AD and can be used to manifest solar activity in the past millennium. However, the temporal distribution of the 6,262 auroral records during 1000 and 1900 AD is seriously uneven, with 85.6% of the records appeared after 1700 AD. Here we use the extreme value theory (EVT) to evaluate the effectiveness of characterizing the solar activity with the auroral records before 1700 AD. Due to the inhomogeneity of the auroral records, the EVT has been conducted separately for the data before 1700 and after 1700, finding that the 100‐year auroral frequency is 25.66 [19.67, 33.67] based on the auroral data in 1000–1699, and 283.71 [183.14, 417.58] based on the auroral data in 1700–1900. The predictions of both the 50‐year and 100‐year auroral frequencies before 1700 AD agree well with the solar activity index.

An application of artificial intelligence for investigating the effect of COVID-19 lockdown on three-dimensional temperature variation in equatorial Africa

We present interesting application of artificial intelligence for investigating effect of the COVID-19 lockdown on 3-dimensional temperature variation across Nigeria (2°–15° E, 4°–14° N), in equatorial Africa. Artificial neural networks were trained to learn time-series temperature variation patterns using radio occultation measurements of atmospheric temperature from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC). Data used for training, validation and testing of the neural networks covered period prior to the lockdown. There was also an investigation into the viability of solar activity indicator (represented by the sunspot number) as an input for the process. The results indicated that including the sunspot number as an input for the training did not improve the network prediction accuracy. The trained network was then used to predict values for the lockdown period. Since the network was trained using pre-lockdown dataset, predictions from the network are regarded as expected temperatures, should there have been no lockdown. By comparing with the actual COSMIC measurements during the lockdown period, effects of the lockdown on atmospheric temperatures were deduced. In overall, the mean altitudinal temperatures rose by about 1.1 °C above expected values during the lockdown. An altitudinal breakdown, at 1 km resolution, reveals that the values were typically below 0.5 °C at most of the altitudes, but exceeded 1 °C at 28 and 29 km altitudes. The temperatures were also observed to drop below expected values at altitudes of 0–2 km, and 17–20 km.

A Reconstruction of Total Solar Irradiance Based on Wavelet Analysis

AbstractAs an important indicator of solar activity, the long‐term total solar irradiance (TSI) observations are needed to uncover the impact of solar activity on Earth's climate. In this paper, the periodic variation of TSI and its relationships with sunspot number and Ca II K index are analyzed by using the satellite observation data from 1979 to 2015 and the wavelet method. The results of continuous wavelet analysis show that TSI, sunspot number and Ca II K index all have significant and stable oscillation periods of 9∼13 years and intermittent oscillation periods of 2∼6 months only during the time of intense solar activity. Moreover, the results of cross wavelet analysis indicate that the effect of sunspot number and Ca II K index on TSI is mainly reflected in the period of 9∼13 years with one month phase lag, and sunspot number and Ca II K index cannot explain the TSI variation in the period of 3∼6 months. Under the condition of considering the phase relationship and the model order, the TSI reconstruction model is established and the monthly TSI time series from 1907 to 1978 is restored.

Zonal harmonics of solar magnetic field for solar cycle forecast

According to the scheme of action of the solar dynamo, the poloidal magnetic field can be considered a source of production of the toroidal magnetic field by the solar differential rotation. From the polar magnetic field proxies, it is natural to expect that solar Cycle 25 will be weak as recorded in sunspot data. We suggest that there are parameters of the zonal harmonics of the solar surface magnetic field, such as the magnitude of the l=3 harmonic or the effective multipole index, that can be used as a reasonable addition to the polar magnetic field proxies. We discuss also some specific features of solar activity indices in Cycles 23 and 24.

Rieger-type periodicity in the total irradiance of the Sun as a star during solar cycles 23–24

Context. Total solar irradiance allows for the use of the Sun as a star for studying observations of stellar light curves from recent space missions. Aims. We aim to study how the mid-range periodicity observed in solar activity indices influences the total solar irradiance. Methods. We studied periodic variations of total solar irradiance based on SATIRE-S and SOHO/VIRGO data during solar cycles 23–24 on timescales of Rieger-type periodicity. Then we compared the power spectrum of oscillations in the total solar irradiance to those of sunspot and faculae data to determine their contributions. Results. Wavelet analyses of TSI data reveal strong peaks at 180 days and 115 days in cycle 23, while cycle 24 showed periods of 170 days and 145 days. There are several periods in the sunspot and faculae data that are not seen in total solar irradiance as they probably cancel each other out through simultaneous brightening (in faculae) and darkening (in sunspots). Rieger-type periodicity is probably caused by magneto-Rossby waves in the internal dynamo layer, where the solar cyclic magnetic field is generated. Therefore, the observed periods in the total solar irradiance and the wave dispersion relation allow us to estimate the dynamo magnetic field strength as 10–15 kG. Conclusions. Total solar irradiance can be used to estimate the magnetic field strength in the dynamo layer. This tool can be of importance in estimating the dynamo magnetic field strength of solar-like stars using light curves obtained by space missions.

Hemispheric sunspot numbers 1874–2020

Context. Previous studies show significant north–south asymmetries for various features and indicators of solar activity. These findings suggest some decoupling between the two hemispheres over the solar cycle evolution, which is in agreement with dynamo theories. For the most important solar activity index, the sunspot numbers, so far only limited data are available for the two hemispheres independently. Aims. The aim of this study is to create a continuous series of daily and monthly hemispheric sunspot numbers (HSNs) from 1874 to 2020, which will be continuously expanded in the future with the HSNs provided by SILSO. Methods. Based on the available daily measurements of hemispheric sunspot areas from 1874 to 2016 from Greenwich Royal Observatory and National Oceanic and Atmospheric Administration, we derive the relative fractions of the northern and southern activity. These fractions are applied to the international sunspot number (ISN) to derive the HSNs. This method and obtained data are validated against published HSNs for the period 1945–2004 and those provided by SILSO for 1992 to 2016. Results. We provide a continuous data series and catalogue of daily, monthly mean, and 13-month smoothed monthly mean HSNs for the time range 1874–2020 –fully covering solar cycles 12 to 24– that are consistent with the newly calibrated ISN (Clette et al., 2014). Validation of the reconstructed HSNs against the direct data available since 1945 reveals a high level of consistency, with Pearson correlation coefficients of r = 0.94 (0.97) for the daily (monthly mean) data. The cumulative hemispheric asymmetries for cycles 12–24 give a mean value of 16%, with no obvious pattern in north–south predominance over the cycle evolution. The strongest asymmetry occurs for cycle no. 19, in which the northern hemisphere shows a cumulated predominance of 42%. The phase shift between the peaks of solar activity in the two hemispheres may be up to 28 months, with a mean absolute value over cycles 12–24 of 16.8 months. The phase shifts reveal an overall asymmetry of the northern hemisphere reaching its cycle maximum earlier (in 10 out of 13 cases), with a mean signed phase shift of −7.6 months. Relating the ISN and HSN peak growth rates during the cycle rise phase with the cycle amplitude reveals higher correlations when considering the two hemispheres individually, with r ≈ 0.9. Conclusions. Our findings provide further evidence that to some degree the solar cycle evolves independently in the two hemispheres, and demonstrate that empirical solar cycle prediction methods can be improved by investigating the solar cycle dynamics in terms of the HSN evolution.

The impact of solar activity on ambient ultrafine particle concentrations: An analysis based on 19-year measurements in Boston, USA

Solar radiation plays a major role in atmospheric photochemistry, contributing to the formation and growth of ultrafine particles (PN). PN affect global Earth's radiation balance, climate system, and human health. However, the impact of solar activity on ambient PN remains unclear. In this study, we investigated the associations between daily ambient PN concentrations [particle number (PN)/cm3] and solar radio flux [solar activity index (F10.7 in sfu)] as a solar activity parameter, shortwave solar radiation (SWR), daylight time (DL), cosmic ray-induced ionization (CRII), and air pollution [PM2.5, black carbon (BC) and SO2] over a 19-year period in Boston, MA. We used generalized additive models adjusted for local environmental conditions. We found that F10.7 was the strongest predictor for daily PN concentrations over all time lags (0–28 days of lags) and seasons. The effects were higher in winter and fall. In winter, an interquartile (IQR) of 60 sfu F10.7 corresponded to an increase of 5770 PN/cm3 in the day of PN collection. In fall, an IQR of 75.5 sfu F10.7 was associated with an increase of 5429 PN/cm3. The effects of F10.7 on PN concentrations were slightly greater when the models were adjusted for air pollution. In summer, ambient PN concentrations were statistically significantly associated with F10.7, SWR, and BC, with the strongest association found for PN and BC in the day of PN collection. Unlike the effects of F10.7, SWR and local pollutants on PN concentrations, DL and CRII were negatively associated with ambient PN in the analyses. These findings suggest that solar activity may have a significant impact on daily ambient PN concentrations that affect the Earth's climate system and human health.

Scaling Properties and Persistence of Long-Term Solar Activity

The long-range correlations associated with the presence of persistence are investigated by applying the detrended fluctuation analysis (DFA) on three different proxies of long-term solar activity. The considered datasets are a sunspot number reconstruction (SNR04) obtained from the atmospheric activity of the cosmogenic isotope 14C derived from tree rings, a total solar irradiance reconstruction (TSIR12) obtained from several 10Be ice core records from Greenland and Antarctica in combination with the global record of 14C in tree rings and a new multi-proxy sunspot number reconstruction (SNR18), also derived from 10Be datasets and the global 14C production series. The DFA scaling exponents found for the three time series are similar (lying in the range between 0.70 and 0.77) and the scaling ranges are comparable. These results indicate the presence of long-range correlations with persistence, in substantial agreement with the findings of previous studies carried out on other solar activity indices and proxies.

CONSUMPTION AND USE OF OXYGEN BY THE BODY OF PERSONS WITH CARDIOVASCULAR PATHOLOGY WITH CHANGES IN GEOMAGNETIC ACTIVITY

The aim of the study was to identify and evaluate the relationship between the indicators of solar activity, the content of magnesium in the blood and the level of oxygen utilization by tissues in men with different temperaments and anxiety, suffering from arterial hypertension. During the period of the study from 1995 to 2015, sick and healthy men were divided into equal groups with a predominance of choleric, sanguine, phlegmatic and melancholic temperament with high and low anxiety. The average annual values of the Wolf numbers, the radio emission of the Sun at a wavelength of 10,7 cm, atmospheric pressure, gamma background and air temperature were taken into account, and the content of magnesium and hemoglobin in the blood serum was determined. The oxygen concentration was determined by the calculated method. A statistically significant direct correlation has been established between the increase in solar activity (Wolf numbers, radio emission flux at a wavelength of 10.7 cm), on the one hand, and atmospheric pressure, air temperature, and the gamma background of the environment, on the other. Under the same environmental conditions, the content of magnesium in the blood and the level of oxygen utilization by the body tissues of patients with arterial hypertension decreased in the temperamental range from high- and low-anxiety sympathotonics (choleric and sanguine) to parasympathotonics (high- and low-anxiety phlegmatic and melancholic). During the study period, a statistically significant relationship was established between an increase in solar activity (Wolf numbers, radio emission flux), atmospheric pressure, air temperature, and gamma background, on the one hand, and a decrease in the content of magnesium in the blood, as well as the level of oxygen utilization by tissues in healthy high- and low-anxiety individuals and patients with arterial hypertension, regardless of temperament.

Moon Mapping Project Results on Solar Wind Ion Flux and Composition

The “Moon Mapping” project is a collaboration between the Italian and Chinese Governments allowing cooperation and exchange between students from both countries. The main aim of the project is to analyze remotely-sensed data collected by the Chinese space missions Chang’E-1/2 over the Moon surface. The Italian Space Agency is responsible for the Italian side and the Center of Space Exploration, while the China Ministry of Education is responsible for the Chinese side. In this article, we summarize the results of the “Moon Mappining” project topic #1: “map of the solar wind ion” using the data collected by Chang’E-1 satellite. Chang’E-1 is a lunar orbiter, its revolution period lasts 2 h, and its orbit is polar. The satellite is equipped with two Solar Wind Ion Detectors (SWIDs) that are two perpendicular electrostatic spectrometers mapping the sky with a field of view of 15° × 6.7° × 24 ch. The spectrometers can measure solar wind flux in the range 40 eV/q–17 keV/q with an energy resolution of 8% and time resolution of ∼3 s. The data collected by the two Solar Wind Ion Detectors are analyzed to characterize the solar wind flux and composition on the Moon surface and to study the time variations due to the solar activity. The data measured by Chang’E-1 compared with the one measured in the same period by the electrostatic spectrometers onboard the ACE satellite, or with another solar activity indicator as the sunspot number, enrich the multi-messenger/multi-particle view of the Sun, gathering valuable information about the space weather outside the Earth magnetosphere.

Prediction of Equatorial Electrojet Based on the Neural Network during Quiet Time

In this study, BP neural network technology was used to predict the variations of Equatorial Electrojet (EEJ) of Indian sector, Peruvian sector and CHAMP satellite during the magnetic quiet pe-riod after 2008. The neural network training data is the corresponding observation data of EEJ during the period of magnetic quiet from 2000 to 2007. The input parameters are day of year, local time, solar zenith angle, solar activity index (<italic>F</italic>_10.7), lunar age and satellite geographic longitude, and the output parameters are EEJ. The EEJ prediction results are statistically analyzed and compared with the observation results. Results show that: BP neural network has good ability in predicting the variations of EEJ in the event, and the prediction results can reflect the important distribution characteristics of EEJ; there is very good correlation between the predicted values and the observed values of EEJ, and the correlation coefficient between the observed values and the predicted values of geomagnetic sta-tions can reach over 85%. In addition, the prediction results of BP neural network model are compared with those of Yamazakis empirical model, and the performance of BP neural network is equivalent with Yamazakis empirical model. The results show that BP neural network has excellent performance in predicting EEJ variations during quiet period, and has a good application prospect.

BoxCox multi-output linear regression for 10.7 cm solar radio flux prediction

We consider the problem of predicting the mid-term daily 10.7cm solar radio flux (F10.7), a widely-used solar activity index. A novel approach is proposed for this task, in which BoxCox transformation with a proper parameter is first applied to make the data satisfy the property of homoscedasticity that is a basic assumption of regression models, and then a multi-output linear regression model is used to predict future F10.7 values. The experiment shows that the BoxCox transformation significantly improves the predictive performance and our new approach works substantially better than the prediction from the US Airforce and other alternative methods like Auto-regressiveModel, Multi-layer Perceptron, and Support Vector Regression.

Solar Extreme and Far Ultraviolet Radiation Modeling for Aeronomic Calculations

Modeling the upper atmosphere and ionospheres on the basis of a mathematical description of physical processes requires knowledge of ultraviolet radiation fluxes from the Sun as an integral part of the model. Aeronomic models of variations in the radiation flux in the region of extreme (EUV) and far (FUV) radiation, based mainly on the data of the last TIMED mission measurements of the solar spectrum, are proposed. The EUVT model describes variations in the 5–105 nm spectral region, which are responsible for the ionization of the main components of the earth’s atmosphere. The FUVT model describes the flux changes in the 115–242 nm region, which determines heating of the upper atmosphere and the dissociation of molecular oxygen. Both models use the intensity of the hydrogen Lyman-alpha line as an input parameter, which can currently be considered as one of the main indices of solar activity and can be measured with relatively simpler photometers. A comparison of the results of model calculations with observations shows that the model error does not exceed 1–2% for the FUVT model, and 5.5% for EUVT, which is sufficient for calculating the parameters of the ionosphere and thermosphere.

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

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

Temporal and spatial characteristics of the ionosphere in the Qinghai–Tibet Plateau

The ionosphere characteristics are important for radio propagation and to monitor climate. At present, its research is confined to global scale or a single station. There are only few local area studies of ionosphere. In view of this situation, we will first verify the reliability of Global Ionosphere Map (GIM, IGS final products) in the Qinghai–Tibet Plateau, then implement low-power filtering and time series analysis to study the periodic, semiannual, and seasonal variation, the peak characteristic, and the “winter anomaly” phenomenon of the ionosphere. Finally, correlations between total electron content (TEC), solar activity indices, and geomagnetic indices are investigated, respectively, by executing quadratic polynomial fitting and establishing the relationship of TEC and F10.7p. The experimental results show that GIM is a reliable resource to research on the temporal and spatial characteristics of the ionosphere in the Qinghai–Tibet Plateau. The minimum TEC always occurs in autumn, whereas the maximum TEC occurs in spring or winter alternatively, which depends on the ascending or descending phase of solar activity. The “winter anomaly” phenomenon that existed for few years normally appears during the ascending phase of solar activity. The correlation coefficients of TEC with three solar activity indices, sunspot number, F10.7, and F10.7p are 0.79, 0.82, and 0.83, respectively, which show strong correlations between them. The correlation coefficients of TEC with three geomagnetic indices, Dst, Kp, and Ap are −0.48, 0.43, and 0.38, respectively, which show weak correlations between them. Quadratic polynomial regression of F10.7p and TEC is implemented. The regression line reflects that the ionosphere TEC in the Qinghai–Tibet Plateau has a saturated status.