Sunspot Number Research Articles

Exploring the Dynamic Rotational Profile of the Hotter Solar Atmosphere: A Multiwavelength Approach Using SDO/AIA Data

Understanding the global rotational profile of the solar atmosphere and its variation is fundamental to uncovering a comprehensive understanding of the dynamics of the solar magnetic field and the extent of coupling between different layers of the Sun. In this study, we employ the method of image correlation to analyze the extensive data set provided by the Atmospheric Imaging Assembly of the Solar Dynamic Observatory in different wavelength channels. We find a significant increase in the equatorial rotational rate (A) and a decrease in absolute latitudinal gradient (∣B∣) at all temperatures representative of the solar atmosphere, implying an equatorial rotation up to 4.18% and 1.92% faster and less differential when compared to the rotation rates for the underlying photosphere derived from Doppler measurement and sunspots respectively. In addition, we also find a significant increase in equatorial rotation rate (A) and a decrease in differential nature (∣B∣ decreases) at different layers of the solar atmosphere. We also explore a possible connection from the solar interior to the atmosphere and interestingly found that A at r = 0.94 R ⊙ and 0.965 R ⊙ show an excellent match with 171 Å, 304 Å, and 1600 Å, respectively. Furthermore, we observe a positive correlation between the rotational parameters measured from 1600 Å, 131 Å, 193 Å, and 211 Å with the yearly averaged sunspot number, suggesting a potential dependence of the solar rotation on the appearance of magnetic structures related to the solar cycle or the presence of cycle dependence of solar rotation in the solar atmosphere.

Heliospheric Effect on Solar Activity Parameters during MaximumPhase of Solar Cycle 24 (2012-2015)

Abstract The time series of daily data of solar activity proxies, namely the sunspot number (SSN), sunspot area (SSA), solar radio flux (F10.7), modified coronal index (MCI), solar flare index (FI), and cosmic ray intensity (CRI), were analyzed to understand the solar activity modulations and short-term periodicities therein. Rieger-type, and other short-term periods, including the solar rotational period that covers the maximum activity phase period (maximum phase of solar cycle 24). The wavelet power spectra and Periodogram of SSN, SSA, F10.7, MCI, FI, and CRI exhibited a significant short-term period. The heliospheric effects exist for a particular period (~27 days) and it is related to the solar activity phenomena. The cross-correlation coefficients and time lags between the cosmic ray intensity and solar activity parameters were estimated to be 200, 46, 281, 39, and 47 days for SSN, SSA, F10.7, MCI, and FI respectively during the time series 2012-2015 (maximum phase of solar cycle 24).

Correlation analysis of the long-term interplay of cosmic rays, solar activity, and solar irradiance

Abstract This study presents a comprehensive analysis of the interplay between solar irradiance variability, solar activity, and cosmic rays over an extensive period from 1950 to 2023, well beyond the scope of previous research that focused on fewer solar cycles. Besides, using a robust dataset, we investigated the correlation between solar activity, represented by sunspot numbers, and the total solar irradiance, alongside the influence of cosmic rays. In this respect, our methodology incorporated sophisticated statistical techniques, including correlation analysis and linear regression, in order to elucidate the complex relationships among these variables. We identified a strong positive correlation between solar activity and total solar irradiance r ≈ + 0.95 , together with a significant anti-correlation between solar activity and cosmic rays r ≈ − 0.72 as well as cosmic rays and total solar irradiance r ≈ − 0.67 . As a consequence, the results of this study offer new insights into the long-term solar influence on climate through cosmic rays, enhancing our understanding of the Sun-Earth dynamic over prolonged periods. Likewise, the extended time series and the analytical framework developed in this study pave the way for further research into related phenomena, including the effects of cloud cover and potential links between cosmic rays and climate change.

Restoring historical moose densities results in fewer wolves killed for woodland caribou conservation

AbstractWoodland caribou (Rangifer tarandus caribou) are declining across much of their distribution in Canada in response to habitat alteration, leading to unsustainable predation, particularly by wolves (Canis lupus). Habitat alteration can benefit the primary prey species of wolves (moose [Alces alces] and deer [Odocoileus spp.]) by creating early seral conditions that contain more of their preferred food types. This increase in primary prey populations results in elevated wolf abundance and heightened predation pressure on caribou. In response to the elevated wolf populations and the risks to caribou, managers have reduced wolf abundance in key areas. Ecological theory suggests that reducing wolf abundance would release moose from the top‐down effects of wolf predation, potentially allowing moose populations to grow. Elevated moose abundance thus has the potential to cause wolf populations to rebound quickly each year following reductions, suggesting a possible link between moose abundance and the number of wolves killed for caribou conservation. To test this idea we used a unique management situation in British Columbia and Alberta, Canada, where lethal wolf removals were annually conducted across specific southern mountain caribou population ranges and, in some places, moose populations were concurrently reduced via liberalized hunting. We used indices of moose abundance and wolf removal data to test the hypothesis that reducing moose populations to a historical abundance target by hunting leads to fewer wolves killed for caribou conservation. After controlling for habitat quality, wolves removed per km2 was 3.2 times lower in areas with reduced moose density ( = 1.55 wolves/1,000 km2 ± 0.33 [SE]) than in those without reduced moose density ( = 5.02 wolves/1,000 km2 ± 0.52). However, the average number of wolves removed per year decreased under both conditions. After 9 years, there was a 35% reduction in the predicted difference in the annual removal between areas with and without moose reduction. Our results suggest that policies that do not reduce or stabilize moose abundance will result in the removal of more wolves to increase caribou abundance. Like wolf reductions, moose reductions can also be controversial and affect local harvesters. Thus, understanding the consequences of actions that support caribou recovery is essential to supporting evidence‐based policy discussions.

Statistical Study of the Occurrence of Coronal Holes in the Solar Corona During Solar Cycle 24

In this article we look at: (a) the occurrence of coronal holes as a function of the different phases of solar cycle 24, (b) the variability of the annual number of coronal holes from 2009 to 2019, (c) the distribution of polar and non-polar coronal holes, irrespective of the phase but also as a function of the different phases of the cycle. From the phase minimum to the descending phase of solar cycle 24, the occurrences of coronal holes observed on the solar disc are 38%, 24%, 9% and 29% respectively. The annual number of coronal holes observed on the solar disc does not always follow the expected evolution of the two components of the solar magnetic field and the annual number of sunspots. Regardless of the phase of the solar cycle, the majority of coronal holes, around 65%, are located in the polar regions. During the early and late phases of the solar cycle, polar coronal holes predominate, whereas during the ascending phase and phase maximum, non-polar coronal holes predominate. The number of polar coronal holes is highest during the minimum phase of the solar cycle and lowest during the maximum phase. During the phases of the solar cycle, coronal hole activity appears to be in phase opposition with sunspot activity. There is a fairly good correlation between variations in the number of polar coronal holes and the expected evolution of the poloidal component of the solar magnetic field.

Detrimental impact of solar and geomagnetic activity on plasma B-complex vitamins in the VA normative aging study cohort

It has been hypothesized that ultraviolet (UV) radiation can lead to depletion of plasma folate and B12 vitamin, but few studies have investigated effects of other parameters of solar and geomagnetic activity (SGA). We investigated the association between four SGA parameters—interplanetary magnetic field (IMF), sunspot number (SSN), Kp index, and ground shortwave solar radiation (SWR)—and three plasma B-complex vitamins—folate, B6, and B12—in 910 participants from the Normative Aging Study (NAS) between 1998 and 2017. Mixed-effects regression models were used for 1- to 28-moving day averages of SGA exposure, adjusted for covariates. We compared the impact of SGA in individuals under higher and lower B-complex supplementation (> or < 50th quartile). Our findings show that increases in solar activity variables IMF and SSN were found to be significantly associated with decreases in B12 vitamin. IMF and SSN were associated with decrease in folate levels, especially in individuals under higher levels of B-complex supplementation. No associations were found for SWR and Kp index. To our knowledge, this is the first study that demonstrated the detrimental impact of solar activity on plasma B12 and folate in a large cohort. These findings have clinical implications during periods of high solar activity.

No Maunder Minimum phase in HD 4915

The long-term solar magnetic activity and its cyclical behaviour, which is maintained by a dynamo mechanism, are both still challenging problems for astrophysics. In particular, an atypical event occurred between 1645 and 1715, when the solar activity was remarkably decreased and the number of sunspots was extremely reduced. However, the exact events that unfolded during the solar cycle remain unclear. The discovery of longer activity minima in cool stars may shed light on the nature of the complex mechanisms involved in the long-term behaviour of the solar-stellar dynamo. Our aim is to explore whether the G5V solar-like star HD\,4915, which showed a striking chromospheric activity pattern in a previous study performed with HIRES data, might be considered a bona fide Maunder Minimum (MM) candidate. We analysed over 380 spectra acquired between 2003 and 2022 using the HARPS and HIRES spectrographs. We carried out a detailed search for activity signatures in HD\,4915 by using the Mount Wilson and the Balmer alpha $ activity indexes. This task was performed by means of the generalised Lomb-Scargle periodogram. The new HARPS data show that the chromospheric activity of HD 4915 is not decreasing. In fact, the increases in the activity after the broad minimum in three years reaches the level of activity before this phase, suggesting that it is not entering an MM phase. We also calculate a rotation period of $23.4 0.2$ d, which has not been reported before. HD\,4915 shows a distinctive activity behaviour that was initially attributed to a possible and incipient MM phase. Additional HARPS data allowed us to discard an MM in the star. Our analysis shows that the complex activity pattern of HD\,4915 might be ruled by a multiple activity cycle, in which a shorter cycle of 4.8 yr is modulated by a potential longer cycle. More activity surveys with extensive records and suitable cadence are crucial for an accurate identification of stars in magnetic grand minima.

Wolf population density: prey biomass limits via intrinsic factors

Whether gray wolf Canis lupus population density is limited intrinsically or extrinsically has occupied researchers for decades. Since 1983, prey biomass, an extrinsic factor, has been accepted as limiting, but that conclusion was recently challenged for unusually high wolf densities which were then said to be limited by behavioral, or intrinsic, factors such as intraspecific strife, dispersal, etc., below prey‐biomass constraints. That contention has been disputed, so disagreement remains. This article discusses the models involved, presents revised models that shed new light, and offers evidence that supports the conclusion that at least at densities below 79 wolves 1000 km−2, wolf numbers per area are limited by prey biomass. As wolf density increases, behavioral factors limit the density to the number of wolves the prey biomass will support. Extra wolves disperse, and wolf range expands. Thus, while wolf density is self‐limiting, the population is not.

A comparative Analytical Investigation of Different Geomagnetic Storms During Solar Cycles 23 and 24

Abstract In this work, the geomagnetic storms that occurred during solar cycles 23 and 24 were classified based on the value of the Disturbance Storm Time index (Dst), which was considered an indicator of the strength of geomagnetic conditions. The special criterion of Dst &gt;-50 nT was adopted in the classification process of the geomagnetic storms based on the minimum daily value of the Dst-index. The number of geomagnetic storms that occurred during the study period was counted according to the adopted criteria, including moderate storms with (Dst &gt;-50 nT), strong storms with (Dst &gt;-100 nT), severe storms with (Dst &gt;-200 nT), and great storms with (Dst &gt;-350 nT). The statistical results showed that the total number of geomagnetic storms identified during solar cycle 23 was 571 storms, while during solar cycle 24, the number of storms decreased to 282 storms. Depending on the minimum value of Dst-index, the geomagnetic storms identified during Cycle 23 were classified into: 446 moderate, 101 strong, 19 severe, and 5 great storms. During Cycle 24, it was classified into: 247 moderate, 34 strong, and 1 severe storm. Also, the results of the study indicated that no storm of either a severe or great type was recorded during the solar cycle 24, given that this cycle witnessed low solar activity. This indicates that solar activity associated with sunspot number (SSN) corresponds to the rate of occurrence and strength of geomagnetic storms of all categories.

Modeling of the Variability of D‐Region Ionospheric Electron Density During Solar Cycle‐24

AbstractSolar cycle variation of earth's atmosphere, particularly the ionosphere is of particular interest in the field of space science and space weather studies. In this article, we present the outcome of our detailed quantitative study on solar cycle variation of lower ionospheric properties using numerical investigation. First, we seek to model and compare the collective D‐region ionization rates (’s) due to the individual contributions from the ionizing sources, namely, (a) solar extreme ultraviolet (EUV) radiation including the Lyman‐ irradiation and (b) solar X‐ray irradiation throughout the solar cycle (C24). Then, we compute the electron density profiles using the ionization rates. We report significant solar cycle variation in ionization rate and electron density profiles for the entire span of C24. We use the sunspot number (SPN) profile to substantiate the finer details of profile during C24. For the segments of the D‐region above two different geographic coordinates, we report that profiles show a consistent “dual peak” nature. It is very similar to the SPN profile during C24. As a next‐order validation, we compare our modeled profiles with their IRI‐2020 counterpart (s). Their overall trends are found to be in agreement. Finally, we discuss the response of the D‐region in terms of due to C24. The work lays the foundation for our upcoming studies on D‐region response to solar cycle variation with Very Low Frequency (VLF) observation.

Enhancing Solar Cycle 25 and 26 Forecasting with Vipin-Deep-Decomposed-Recomposed Rolling-window (vD2R2w) Model on Sunspot Number Observations

Enhancing Solar Cycle 25 and 26 Forecasting with Vipin-Deep-Decomposed-Recomposed Rolling-window (vD2R2w) Model on Sunspot Number Observations

Autocorrelations of the Wolf Number Cycle Fragments and Solar Half-Cycle Forecast

Autocorrelations of the Wolf Number Cycle Fragments and Solar Half-Cycle Forecast

Temporal variation of atmospheric electric field in comparison with solar terrestrial activities during the 24th solar cycle

Solar activities play an important role in the variation of the Atmospheric Electric Field (AEF), and affect the Global Electric Circuit (GEC). The relationship between the variation of the AEF and solar activities is focused in the present study. It includes the variation in the AEF with respect to sunspot numbers, direct and indirect radiations, and solar flares during the decline phase of solar cycle 24 from 2015–2019 for Islamabad (ISL) observatory in detail, and partially for Muzaffarabad (MZF) observatory. A few of them had good relationship with the atmospheric electric field. The solar eclipse effect on the atmospheric electric field for the Muzaffarabad station is also presented in this work. A significant increase was observed during the eclipse period which led to decrease in electrical conductivity of atmospheric electric field as compared to alternate days for the same period.

Крупномасштабные связи геомагнитных индексов SYM-H и ASY-H с северо-южной компонентой ММП и бета-параметром солнечного ветра

Using annual average values, the relationships are examined of the geomagnetic indices SYM-H, ASY-H, and Dst with solar wind parameters in 1981–2015. The data used was divided into two samples according to the sign of the north-south component Bn of the interplanetary magnetic field (IMF). Variations in the annual average values of each of the Dst, SYM-H, and ASY-H indices for southward and northward IMF have been found to be similar and their linear correlation coefficients r to be high: 0.871, 0.863, and 0.943 respectively. The similarity between variations of the indices with different signs of Bn is probably due to their connection with the number of sunspots. It has been established that Dst, SYM-H, and ASY-H depend on the solar wind parameter β: their absolute values decrease with increasing β, regardless of Bn sign. The decrease in the indices with increasing β is likely to be caused by the transition of the magnetosphere to a quiet state due to the increasing predominance of thermal pressure over magnetic one in the solar wind and a decrease in the level of solar wind turbulence. SYM-H and ASY-H have been found to reveal the closest relationships with β, whereas SYM-H more strongly depends on β for southward IMF (r=0.744) than for northward IMF (r=0.677). On the contrary, for ASY-H r=–0.741 at northward IMF and r=–0.719 at southward IMF. Similar to SYM-H, Dst (to a lesser extent) significantly correlates with β at southward IMF (r=0.629) and weaker at northward IMF (r=0.456).

Large-scale relationships of the geomagnetic indices SYM-H and ASY-H with the north-south IMF component and the solar wind beta parameter

Using annual average values, the relationships are examined of the geomagnetic indices SYM-H, ASY-H, and Dst with solar wind parameters in 1981–2015. The data used was divided into two samples according to the sign of the north-south component Bn of the interplanetary magnetic field (IMF). Variations in the annual average values of each of the Dst, SYM-H, and ASY-H indices for southward and northward IMF have been found to be similar and their linear correlation coefficients r to be high: 0.871, 0.863, and 0.943 respectively. The similarity between variations of the indices with different signs of Bn is probably due to their connection with the number of sunspots. It has been established that Dst, SYM-H, and ASY-H depend on the solar wind parameter β: their absolute values decrease with increasing β, regardless of Bn sign. The decrease in the indices with increasing β is likely to be caused by the transition of the magnetosphere to a quiet state due to the increasing predominance of thermal pressure over magnetic one in the solar wind and a decrease in the level of solar wind turbulence. SYM-H and ASY-H have been found to reveal the closest relationships with β, whereas SYM-H more strongly depends on β for southward IMF (r=0.744) than for northward IMF (r=0.677). On the contrary, for ASY-H r=–0.741 at northward IMF and r=–0.719 at southward IMF. Similar to SYM-H, Dst (to a lesser extent) significantly correlates with β at southward IMF (r=0.629) and weaker at northward IMF (r=0.456).

Long-term geomagnetic activities and stratospheric winter temperature

In this research, impact of long term solar forcing on stratospheric winter temperature is checked. The 11- year sunspot activity and geomagnetic indices (AE, Kp, Dst) are used as an indicator for solar forcing, as geomagnetic activity indices show good correlation with solar variability. To understand the impact of solar forcing through high latitude, stratospheric winter (November to March) time North Polar Region (60N–90N) temperature anomalies are considered. The findings showed that temperature changes in the stratosphere are significantly correlated with solar activity, as evidenced by a significant positive correlation between the 11-year moving mean of stratospheric (10 hPa) temperature anomalies and sunspot number. Approximately from 1970 to 2000, the North Polar Region saw positive anomalous stratospheric winter temperatures. During the same time, the geomagnetic activity also showed a substantial increase. The year-to-year correlation between stratospheric pole temperature and geomagnetic activity is significant (about 0.5). The Empirical Mode Decomposition analysis reveals a highly significant correlation (around 0.9) between the long-term component of stratospheric winter temperature (IMF-4) and the long-term component of geomagnetic activity (IMF-3 and IMF-4). One of the reasons for the increase in lower stratospheric temperature is an increase in ozone concentration during the same period when geomagnetic activity is higher. Empirical orthogonal function (EOF) and correlation analysis of stratospheric winter temperature with large-scale circulation patterns are also carried out. The spatial correlation is checked for stratospheric winter temperature at North Pole and lower atmospheric levels (250 hPa and 850 hPa) followed by pre-monsoon and monsoon season. This study includes statistical analysis, however, also highlights the necessity of in-depth dynamical analysis to improve our understanding of how solar activity impacts Earth's atmospheric layers, which may be helpful in predicting the weather and climate.

Forecast of Modulation of Cosmic Rays with Rigidity of 10 GV in the 25th Solar Activity Cycle

Based on a forecast of solar activity parameters and the model developed by the authors for modulation of Galactic cosmic rays, we forecasted cosmic ray variations in the 25th solar activity cycle. The cosmic ray flux forecast is based on correlation with the number of sunspots (single-parameter model) or with a set of solar (mainly magnetic) parameters (multiparameter model). The forecast for the number of sunspots was taken from published data; the forecast for other solar parameters was done in the study. It is shown that variations in cosmic rays over three years of the current 25th cycle, in general, do not contradict the forecasts and indicate that the 25th solar activity cycle is expected to be slightly more active compared to the 24th.

Bayesian Knowledge Infusion for Studying Historical Sunspot Numbers

A scientific method that proposes a value Y to estimate a target value ρ is often subject to some level of uncertainty. In the Bayesian framework, the level of uncertainty can be measured by the width of the 68% interval, which is the range of the middle 68% of the ranked ρ values sampled from the posterior distribution p(ρ|Y). This paper considers Bayesian knowledge infusion (BKI) to reduce the uncertainty of the posterior distribution p(ρ|Y) based on additional knowledge that an event A happens. BKI is achieved by using a conditional prior distribution p(ρ|A) in the Bayes theorem, assuming that given the true ρ, its error-contaminated value Y is independent of event A. We use two examples to illustrate how to study whether or not it is possible to reduce uncertainty from 14C reconstruction (Y) of the annual sunspot number (SSN) (ρ) by infusing additional information (A) using BKI. Information (A) that SSN is from a year that has a Far Eastern record of naked eye sunspots is found to be not so effective in reducing the uncertainty. In contrast, information that SSN is from a year at a cycle minimum is found to be very effective, producing much narrower 68% intervals. The resulting Bayesian point estimates of SSN (the posterior medians of ρ) are cross-validated and tested on a subset of telescopically observed SSNs that were unused in the process of Bayes computation.

Determining the maximum of solar cycle 25 with a memory modulated white noise

The exact determination of the solar maximum of a solar cycle before it occurs remains an open problem in solar physics. Using a memory modulated white noise framework, a procedure is presented to determine the still unknown solar maximum of solar cycle 25. We investigate the first thirty months of each of the past 24 solar cycles from 1755 to 2019 using a second order structure function derived from white noise analysis. Specifically, the mean square deviation (MSD) of the fluctuating monthly sunspot numbers for the first 30 months of a solar cycle is matched with the theoretical MSD to obtain a value for the memory parameter μ. By similarly determining the value of μ for the first 30 months of solar cycle 25, a forecast is made for its solar maximum.

Assessment of IRI2020 model accuracy in predicting ionospheric parameters: Insights from multiple ionosonde stations

This research assesses the performance of the IRI2020 model in forecasting the ionospheric critical frequency of the F2 layer (foF2) and Maximum Usable Frequency (MUF) of the ionosphere from 2020 to 2023 across multiple ionosonde stations. The primary objective is to analyse the characteristics of foF2 and MUF across various longitudinal sectors during the solar minimum to ascending phase of solar cycle 25 and to evaluate the IRI2020 model’s performance in replicating observed data. Additionally, the study explores the influence of various space weather parameters on the variability of these ionospheric parameters. The findings reveal that the IRI2020 model overestimates the daily mean values of both foF2 and MUF(3000)F2 across the stations over the three years. While exhibiting good performance in capturing the pattern of hourly predictions, the model tends to overestimate foF2 more than MUF(3000)F2, with better predictions observed for MUF(3000)F2. However, hourly estimations display a mix of underestimation and overestimation, predominantly overestimating values. Correlations ranged from 0.58 to 0.92 for foF2 and 0.72 to 0.91 for MUF(3000)F2, showing variability across stations. As solar activity increases, seasonal variations become more evident, especially in stations located in the northern hemisphere.In contrast, stations in the southern hemisphere exhibit less pronounced seasonal variations, suggesting a notable hemispheric asymmetry. Although the IRI2020 better captured the general trend of foF2 and MUF(3000)F2 in our investigation, the percentage deviation for MUF(3000)F2 ranges from 1 % to 15.1 %, which can result in a significant range reduction for practical applications like HF communications. Stations closer to the geomagnetic equatorial line exhibit stronger seasonal asymmetry and higher deviations. Some key space weather parameters, including sunspot number R, F10.7 and R/F10.7 ratio, were found to significantly influence ionospheric variability, with sunspot number R and R/F10.7 showing a stronger correlation with foF2 and MUF(3000)F2. These suggest that the variability of the solar active region parameters primarily controls ionospheric foF2 and MUF(3000)F2.