Solar Sunspot Number Research Articles

Airborne particle radioactivity during desert dust days in Cyprus

Mediterranean countries are often affected by desert dust storms, which have significant effects on the environment and public health. We compared airborne particle radioactivity levels during desert dust and non-dust days in Cyprus.Gross α- and β-radioactivity from Total Suspended Particle (TSP) samples, collected at two urban routine monitoring stations in Limassol and Nicosia, were available for the period 2017–2020 and 2008–2020, respectively. Radionuclides 137Cs and 40K, from TSP samples, were also available from a semi-industrial monitoring station in Nicosia during 2008–2020. Information on desert dust presence, dust origin, particulate matter (PM) levels, and solar activity (KP index and solar sunspot numbers - SSN) were also obtained. We used linear regression models adjusting for seasonality and long-term trends, and solar activity to assess the effect of dust storms on TSP gross α- and β-, and 137Cs and 40K radioactivity levels.Gross α- and β-radioactivity, and 137Cs and 40K radioactivity levels were significantly higher on days with desert dust compared to days characterized with no influence of desert dust. Levels of gross α- and β-radioactivity during dust days were higher when dust originated from the Middle East deserts than from the Sahara Desert. The same trend was observed for the ratios 137Cs to 40K and 137Cs to PM10. Conversely, ratios of TSP gross α- and β-radioactivity to PM10 were significantly lower during desert dust days in comparison to days without dust influence.This study suggests that desert dust increase both TSP gross α- and β-radioactivity, as well as 137Cs and 40K radioactivity levels. Further studies should clarify the contribution of anthropogenic and other natural sources to the emission or transportation of particles radioactivity, to better mitigate future exposures.

Time Series Prediction of ESN Based on Chebyshev Mapping and Strongly Connected Topology

This paper introduces a novel approach called Chebyshev mapping and strongly connected topology for optimization of echo state network (ESN). To enhance the predictive performance of ESNs for time series data, Chebyshev mapping is employed to optimize the irregular input weight matrix. And the reservoir of the ESN is also replaced using an adjacency matrix derived from a digital chaotic system, resulting in a reservoir with strong connectivity properties. Numerical experiments are conducted on various time series datasets, including the Mackey–Glass time series, Lorenz time series and solar sunspot numbers, validating the effectiveness of the proposed optimization methods. Compared with the traditional ESNs, the optimization method proposed in this paper has higher predictive performance, and effectively reduce the reservoir’s size and model complexity.

Interaction of global electron content with the Sun and solar wind during intense geomagnetic storms

Assessment of solar and solar wind parameters driving the ionosphere model is essential for prediction of the ionospheric weather. In the present paper impact of the different solar, interplanetary and geomagnetic parameters on the global electron content (GEC) during intense space weather storms is investigated. Hourly GEC values are calculated from JPL global maps of total electron content GIM-TEC from 1995 to 2023. The sample comprises 90 intense storms from 1995 to 2023 associated with monthly peak of the weighted accumulation of the geomagnetic Apo(τ, t) index exceeding 90 nT. The 27 day weighted accumulation of the solar sunspot numbers SSN2(τ), solar radio flux F10.7(τ), the solar hydrogen emission Lyman_α(τ) and the composite magnesium MgII(τ) indices are explored as precursors of GEC enhancements. As distinct from the positive ionosphere storm, the solar wind speed Vsw, the solar wind electric field Ey, merging electric field Em and Apo(τ, t) indices proved to be effective as potential drivers of the negative GEC depletion. The positive and negative dGEC deviations from hourly GEC are produced by subtracting a quiet reference GECav averaged during 24h prior the storm normalized by GECav. The hourly storm profiles Vsw(t), Em(t), Ey(t), Apo(τ, t), Dst(t), GEC(t) and dGEC(t) were reduced by method of superposed epochs. The zero epoch t0 = 0 was taken at the peak Apo*(τ, t0) and the storm time lasted for 48h from −12h prior t0 and 35h afterwards. The best correlation of the positive storm dGECp amplitude is obtained with MgII(τ) and the negative storm dGECn with Em* and Apo*(τ, t0) which are used to derive characteristics of five key points of storm-time dGEC(t) model: 1 – onset of the storm profile t1 = t(dGECp); 2 – the amplitude dGECpmax and its time t2(dGECpmax); 3 – the time of transition t3(dGEC = 0) from the positive to negative (±) GEC storm; 4 – minimum negative disturbance dGECnmin and its time t4(dGECnmin), 5 – the end of the storm profile t5(dGECn). Analytical model of dGEC(t) is derived with Epstein step functions fitting 5 key points. Deviations dGEC(t) are inverted to GEC(t) using quiet reference pre-storm GECav. The model is validated for three intense storms on 26–28 February, 23–25 March and 23–25 April 2023. The results show improvement of dGEC forecast with RMS error reduced from 45 to 80% compared to results produced by the international reference ionosphere−plasmasphere model IRI-Plas.

Solar activity: Towards a standard classification of solar phases from cycle 1 to cycle 24

This paper aims to develop a standard classification method of solar phases from Cycles 1 to 24. The purpose is to establish new solar cycle cutting criteria. The maximum sunspot number values (SNmax) of previous criteria were examined. In addition, the evolution of sunspot appearance latitudes (maximum latitude (λ_max) and minimum latitude (λ_min)) was taken into account. This has enabled new criteria to be developed. These criteria take into account the actual Sun' behavior. They also resolve past inconsistencies between classification criteria and new sunspot data. Four phases have been retained: minimum, increasing, maximum and decreasing phases. The new sunspot number (SN) data computed by the Belgian Observatory have been taking into account. SN data set have been smoothed to obtain normalized curves that allowing to represent solar sunspot numbers evolution as a trigonometric function. The mathematical hypotheses formulated concern sunspot appearance latitudes and the identification of the solar cycle. The results show that the different phases do not have the same duration. The increasing phase is quite fast compared to the decreasing one. In fact, the method proposed in this work presents a new cutting criterion as follow: (i) minimum phase: SN(t) < 0.122 × SNmax; (ii) increasing phase: 0.122 × SNmax ≤ SN(t) ≤ 0.73 × SNmax; (iii) maximum phase: SN(t) > 0.73 × SNmax and (iv) decreasing phase: 0.73 × SNmax ≥ SN(t) > SNmin (next cycle).

Cosmic ray intensity variation with solar flare index, solar coronal index and sunspot numbers solar indices during the period of 1986- 2007

Cosmic ray intensity variation with solar flare index, solar coronal index and sunspot numbers solar indices during the period of 1986- 2007

Impact of Solar Activity on Snow Cover Variation Over the Tibetan Plateau and Linkage to the Summer Precipitation in China

Solar activity is one of the main external forcing factors driving the Earth’s climate system to change. The snow cover over the Tibetan Plateau is an important physical factor affecting the East Asian climate. At present, insufficient research on the connection between solar activity and snow cover over the Tibetan Plateau has been carried out. Using Solar Radio Flux (SRF), Solar Sunspot Number (SSN), and Total Solar Irradiance (TSI) data, this paper calculated the correlation coefficients with snow indices over the Tibetan Plateau, such as winter and spring snow depth (WSD/SSD) and snow day number (WSDN/SSDN). These snow indices are obtained from the daily gauge snow data in the Tibetan Plateau. Through correlation analyses, it is found that there are significant synchronous or lag correlations between snow indices and solar parameters on multi-time scales. In particular, the Spring Snow Day Number (SSDN) is of significant synchronous or lag correlation with SRF, SSN, and TSI on multi-time scales. It is further found that SSDN over the Tibetan Plateau has more stable positive correlations with SRF by using the 21-year running mean and cross spectrum analyses. Therefore, SSDN can be ascertained to be the most sensitive snow index to the solar activity compared with other snow indices. Moreover, its influence on summer precipitation of China is strongly regulated by solar activity. In high solar activity years (HSAY), the significant correlated area of summer precipitation in China to SSDN is located further north than that in low solar activity years (LSAY). Such impact by solar activity is also remarkable after excluding the impact of ENSO (i.e., El Niño–Southern Oscillation) events. These results provide support for the application of snow indices in summer rainfall prediction in China.

Active Days around Solar Minimum and Solar Cycle Parameter

Utilizing a new version of the sunspot number and group sunspot number dataset available since 2015, we have statistically studied the relationship between solar activity parameters describing solar cycles and the slope of the linear relationship between the monthly sunspot numbers and the monthly number of active days in percentage (AD). As an effort of evaluating possibilities in use of the number of active days to predict solar activity, it is worthwhile to revisit and extend the analysis performed earlier. In calculating the Pearson’s linear correlation coefficient r, the Spearman’s rank-order correlation coefficient rs, and the Kendall’s τ coefficient with the rejection probability, we have calculated the slope for a given solar cycle in three different ways, namely, by counting the spotless day that occurred during the ascending phase and the descending phase of the solar cycle separately, and during the period corresponding to solar minimum ± 2 years as well. We have found that the maximum solar sunspot number of a given solar cycle and the duration of the ascending phase are hardly correlated with the slope of a linear function of the monthly sunspot numbers and AD. On the other hand, the duration of a solar cycle is found to be marginally correlated with the slope with the rejection probabilities less than a couple of percent. We have also attempted to compare the relation of the monthly sunspot numbers with AD for the even and odd solar cycles. It is inconclusive, however, that the slopes of the linear relationship between the monthly group numbers and AD are subject to the even and odd solar cycles.

Interdecadal correlation of solar activity with Tibetan Plateau snow depth and winter atmospheric circulation in East Asia

Studies on the impact of solar activity on climate system are very important in understanding global climate change. Previous studies in this field were mostly focus on temperature, wind and geopotential height. In this paper, interdecadal correlations of solar activity with Winter Snow Depth Index (WSDI) over the Tibetan Plateau, Arctic Oscillation Index (AOI) and the East Asian Winter Monsoon Index (EAWMI) are detected respectively by using Solar Radio Flux (SRF) , Total Solar Irradiance (TSI) and Solar Sunspot Number (SSN) data and statistical methods. Arctic Oscillation and East Asian winter monsoon are typical modes of the East Asian atmospheric circulation. Research results show that on interdecadal time scale over 11-year solar cycle, the sun modulated changes of winter snow depth over the Tibetan Plateau and East Asian atmospheric circulation. At the fourth lag year, the correlation coefficient of SRF and snow depth is 0.8013 at 0.05 significance level by Monte-Carlo test method. Our study also shows that winter snow depth over the Tibetan Plateau has significant lead and lag correlations with Arctic Oscillation and the East Asian winter monsoon on long time scale. With more snow in winter, the phase of Arctic Oscillation is positive, and East Asian winter monsoon is weak, while with less snow, the parameters are reversed. An example is the winter of 2012/2013, with decreased Tibetan Plateau snow, phase of Arctic Oscillation was negative, and East Asian winter monsoon was strong.

Solar cyclic variability can modulate winter Arctic climate

This study investigates the role of the eleven-year solar cycle on the Arctic climate during 1979–2016. It reveals that during those years, when the winter solar sunspot number (SSN) falls below 1.35 standard deviations (or mean value), the Arctic warming extends from the lower troposphere to high up in the upper stratosphere and vice versa when SSN is above. The warming in the atmospheric column reflects an easterly zonal wind anomaly consistent with warm air and positive geopotential height anomalies for years with minimum SSN and vice versa for the maximum. Despite the inherent limitations of statistical techniques, three different methods – Compositing, Multiple Linear Regression and Correlation – all point to a similar modulating influence of the sun on winter Arctic climate via the pathway of Arctic Oscillation. Presenting schematics, it discusses the mechanisms of how solar cycle variability influences the Arctic climate involving the stratospheric route. Compositing also detects an opposite solar signature on Eurasian snow-cover, which is a cooling during Minimum years, while warming in maximum. It is hypothesized that the reduction of ice in the Arctic and a growth in Eurasia, in recent winters, may in part, be a result of the current weaker solar cycle.

Forty years of solar radio observations at Metsähovi Radio Observatory

The Aalto University Metsähovi Radio Observatory in Finland began regular solar radio observations over 40 years ago, in 1978. It is one of the longest solar radio data collections at millimeter wavelengths, and the data have been widely used in the field of solar radio physics over the years. The main research topics have been microwave solar radio bursts, oscillations, and pulsations in various solar features, for example, radio brightenings and the overall long‐term solar radio variability. Currently, Metsähovi has three different solar radio instruments, operating at wavelengths from 8 mm to 6 m. Most of the observations have been made with the 13.7‐m antenna at 8 mm, but data have also been collected at 3 mm and 1.3 cm. Radio brightenings at 8 mm are a good indicator of the general solar activity level. They show the phase of the solar cycle equally accurately as the traditional solar sunspot number. In this paper, we compare the daily value of the maximum radio brightness temperature and the daily sunspot number in 1989–2017, Solar Cycles 21–24. A more detailed analysis and comparison is performed for Solar Cycle 24 from 2008 onward. We also compare our radio observations to the daily 10.7 cm total radio flux values in Solar Cycle 24.

Mesospheric temperature trends derived from standard phase-height measurements

New homogeneous time series of daily standard phase-height (SPH) and daily plasma scale-height (PSH) have been derived from a 50-year long-radio-wave measurement of the broadcasting station Allouis (France, 162kHz). The signal was received at Kühlungsborn (54°N, 12°E, Mecklenburg, Germany) and the present series is a third release. The daily time series of SPH shows in its spectrum dominant modes which are typical for the solar cycle (SC), for El Niño-Southern Oscillation (ENSO) and for quasi-biannual oscillation (QBO), indicating solar and lower atmospheric influences. Surprisingly, the time series of daily PSH shows a band of dominant cycles larger than 16 years.In order to exclude the influence of the winter anomaly in the determination of column-integrated mesospheric temperature trends the phase-height-temperature procedure is confined to summer months.The derived thickness temperature of the mesosphere decreased statistically significant over the period 1959–2008 after pre-whitening with summer mean of solar sun spot numbers. The trend value is in the order of about −1.05K/decade if the stratopause trend is excluded. The linear regression is more pronounced, −1.35K/decade for the period of 1963–1985 (2 SCs), but weaker, −0.51K/decade during 1986-2008 (last 2 SCs). The linear regression is in very good agreement with a mean column-integrated mesospheric trend derived from OHP-Lidar temperatures on a monthly mean basis for the last two SCs.This clearly shows that the thickness temperature of the mesosphere derived from phase-height measurement is a useful proxy for the long-term summer temperature change in the mesosphere from 1959 until 2008.

Long‐term variation of Ampère force by geomagnetic Sq currents and thermospheric pressure difference

AbstractThe long‐term variation of the Ampère force exerted by geomagnetic Sq currents was studied in relation to the thermospheric pressure. First, the long‐term trend of the pressure difference was estimated using a linear regression coefficient based on a high correlation between the Ampère force and the pressure difference in recent years. The pressure difference may be inferred from solar parameters such as solar sunspot number; inspection of the difference from Sq has a merit that it gives the “response” of the thermosphere in contrast with the “input” parameters of the solar activity index. Next, the effect of the version up of sunspot number was examined. The correlation of the Ampère force with sunspot number updated in 2015 (version 2) is slightly higher than that with old sunspot number (version 1), which suggests that the later version is an improved index for the solar activity and its effect on the state of the thermosphere. Last, the correlation between total Sq currents and sunspot number was found to be less than that between the Ampère force and sunspot number, although the difference is small and could not be statistically significant. This suggests that the geomagnetic main field affects the relation between the Ampère force and the pressure difference.

Wavelet analysis of the singular spectral reconstructed time series to study the imprints of solar–ENSO–geomagnetic activity on Indian climate

Abstract. To study the imprints of the solar–ENSO–geomagnetic activity on the Indian subcontinent, we have applied singular spectral analysis (SSA) and wavelet analysis to the tree-ring temperature variability record from the Western Himalayas. Other data used in the present study are the solar sunspot number (SSN), geomagnetic indices (aa index), and the Southern Oscillation Index (SOI) for the common time period of 1876–2000. Both SSA and wavelet spectral analyses reveal the presence of 5–7-year short-term ENSO variations and the 11-year solar cycle, indicating the possible combined influences of solar–geomagnetic activities and ENSO on the Indian temperature. Another prominent signal corresponding to 33-year periodicity in the tree-ring record suggests the Sun-temperature variability link probably induced by changes in the basic state of the Earth's atmosphere. In order to complement the above findings, we performed a wavelet analysis of SSA reconstructed time series, which agrees well with our earlier results and increases the signal-to-noise ratio, thereby showing the strong influence of solar–geomagnetic activity and ENSO throughout the entire period. The solar flares are considered responsible for causing the atmospheric circulation patterns. The net effect of solar–geomagnetic processes on the temperature record might suggest counteracting influences on shorter (about 5–6-year) and longer (about 11–12-year) timescales. The present analyses suggest that the influence of solar activities on the Indian temperature variability operates in part indirectly through coupling of ENSO on multilateral timescales. The analyses, hence, provide credible evidence of teleconnections of tropical Pacific climatic variability and Indian climate ranging from inter-annual to decadal timescales and also suggest the possible role of exogenic triggering in reorganizing the global Earth–ocean–atmospheric systems.

Sodankylä ionospheric tomography data set 2003–2014

Abstract. Sodankylä Geophysical Observatory has been operating a receiver network for ionospheric tomography and collecting the produced data since 2003. The collected data set consists of phase difference curves measured from COSMOS navigation satellites from the Russian Parus network (Wood and Perry, 1980) and tomographic electron density reconstructions obtained from these measurements. In this study vertical total electron content (VTEC) values are integrated from the reconstructed electron densities to make a qualitative and quantitative analysis to validate the long-term performance of the tomographic system. During the observation period, 2003–2014, there were three to five operational stations at the Fennoscandia sector. Altogether the analysis consists of around 66 000 overflights, but to ensure the quality of the reconstructions, the examination is limited to cases with descending (north to south) overflights and maximum elevation over 60°. These constraints limit the number of overflights to around 10 000. Based on this data set, one solar cycle of ionospheric VTEC estimates is constructed. The measurements are compared against the International Reference Ionosphere (IRI)-2012 model, F10.7 solar flux index and sunspot number data. Qualitatively the tomographic VTEC estimate corresponds to reference data very well, but the IRI-2012 model results are on average 40 % higher than that of the tomographic results.

Correlation between solar activity and the local temperature of Antarctica during the past 11,000 years

The solar impact on the Earth's climate change is a long topic with intense debates. Based on the reconstructed data of solar sunspot number (SSN), the local temperature in Vostok (T), and the atmospheric CO2 concentration data of Dome Concordia, we investigate the periodicities of solar activity, the atmospheric CO2 and local temperature in the inland Antarctica as well as their correlations during the past 11,000 years before AD 1895. We find that the variations of SSN and T have some common periodicities, such as the 208 year (yr), 521yr, and ~1000yr cycles. The correlations between SSN and T are strong for some intermittent periodicities. However, the wavelet analysis demonstrates that the relative phase relations between them usually do not hold stable except for the millennium-cycle component. The millennial variation of SSN leads that of T by 30–40 years, and the anti-phase relation between them keeps stable nearly over the whole 11,000 years of the past. As a contrast, the correlations between CO2 and T are neither strong nor stable. These results indicate that solar activity might have potential influences on the long-term change of Vostok's local climate during the past 11,000 years before modern industry.

Can solar/geomagnetic activity restrict the occurrence of some shellfish poisoning outbreaks? The example of PSP caused by Gymnodinium catenatum at the Atlantic Portuguese coast

Cyclic outbreaks of accumulation of paralytic shellfish poisoning (PSP) toxins in mussels attributed to Gymnodinium catenatum blooms displayed several of the highest inter-annual maxima coincidental with minima of the 11-year solar sunspot number (SSN) cycle. The monthly distribution of PSP was associated with low levels of the solar radio flux, a more quantitative approach than SSN for fluctuations in solar activity. A comparison between monthly distribution of PSP and other common biotoxins (okadaic acid (OA), dinophysistoxin-2 (DTX2) and amnesic shellfish poisoning (ASP) toxins) demonstrated that only PSP was significantly associated with low levels of radio flux (p < 0.01). PSP occurrence suggests a prior decline in solar activity could be required to act as a trigger, in a similar manner to a photoperiodic signal. The seasonal frequency increased towards autumn during the study period, which might be related to the progressive atmospheric cut-off of deleterious radiation associated with the seasonal change in solar declination, and might play an additional role in seasonal signal-triggering. PSP distribution was also associated with low levels of the geomagnetic index Aa. A comparison between monthly distribution of PSP and other common biotoxins, also demonstrated that only PSP was significantly associated with low levels of the Aa index (p < 0.01). In some years of SSN minima no significant PSP-outbreaks in mussels were detected. This was attributed to a steady rise in geomagnetic activity that could disrupt the triggering signal. Global distribution patterns show that hotspots for G. catenatum blooms are regions with deficient crustal magnetic anomalies. In addition to the variable magnetic field mostly of solar origin, static fields related to magnetized rocks in the crust and upper mantle might play a role in restricting worldwide geographic distribution.

Long-term trends in the ionospheric F2 region with different solar activity indices

Abstract. A new comprehensive data collection by Damboldt and Suessmann (2012a) with monthly foF2 and M(3000)F2 median values is an excellent basis for the derivation of long-term trends in the ionospheric F2 region. Ionospheric trends have been derived only for stations with data series of at least 22 years (124 stations with foF2 data and 113 stations with M(3000)F2 data) using a twofold regression analysis depending on solar and geomagnetic activity. Three main results have been derived: Firstly, it could be shown that the solar 10.7 cm radio flux F10.7 is a better index for the description of the solar activity than the relative solar sunspot number R as well as the solar EUV proxy E10.7. Secondly, the global mean foF2 and hmF2 trends derived for the interval between 1948 and 2006 are in surprisingly good agreement with model calculations of an increasing atmospheric greenhouse effect (Rishbeth and Roble, 1992). Thirdly, during the years 2007 until 2009, the hmF2 values and to a smaller amount the foF2 values strongly decrease. The reason for this effect is a reduction of the thermospheric density and ionization due to a markedly reduced solar EUV irradiation and extremely small geomagnetic activity during the solar cycle 23/24 minimum.

North-south asymmetry in solar, interplanetary, and geomagnetic indices

Data of hourly interplanetary plasma (field magnitude, solar wind speed, and ion density), solar (sunspot number, solar radio flux), and geomagnetic indices (Kp, Ap) over the period 1970-2010, have been used to examine the asymmetry between the solar field north and south of the heliospheric current sheet (HCS). A persistent yearly north-south asymmetry of the field magnitude is clear over the considered period, and there is no magnetic solar cycle dependence. There is a weak N-S asymmetry in the averaged solar wind speed, exhibited well at times of maximum solar activities. The solar plasma is more dense north of the current sheet than south of it during the second negative solar polarity epoch (qA < 0). Moreover, the N - S asymmetry in solar activity (Rz) can be statistically highly significant. The sign of the average N - S asymmetry depends upon the solar magnetic polarity. The annual magnitudes of N - S asymmetry depend positively on the solar magnetic cycle. Most of the solar radio flux asymmetries occurred during the period of positive IMF polarity.

Spectral analysis of solar variability and their possible role on global warming

In this study, the effect of solar variability on global warming has been studied. This enables us to understand the existence of solar variability effects on temperature. Monthly, four components that may be closely associated with the climate have been studied, which are geomagnetic activity index aa, solar sunspot number Rz from 1868 - 2008, global surface temperature (GST) from 1880 - 2008 and total solar irradiance TSI from 1978 - 2003. The clear 11-year variation was found in Rz, TSI and aa due to the variation of solar activity, while the 21.3 year variation was found only in GST. It is related to the changes in the polarity of main solar magnetic field, in which the obtained result demonstrates that the interplanetary magnetic field (IMF) effect is more powered on GST. It is believed that the solar and anthropogenic greenhouse forcing are roughly equal contributions to the rise in global temperature during the recent years. Finally, the power law index (n) for Rz and TSI have a higher value than aa and GST. However, this indicates that the modulations of PSD of Rz and TSI are higher than the PSD of the others. Key words: Geomagnetic induction, total solar irradiance, global warming.

Behaviour of the quiet-day geomagnetic variation at Livingston Island and variability of the S q focus position in the South American-Antarctic Peninsula region

Characteristics of the regular daily variation, including seasonal and solar cycle variabilites, at the relatively new geomagnetic observatory of Livingston Island (Antarctica) have been studied. Such studies of solar cycle variability were possible due to the current availability of more than 11 years of definitive data. The seasonal behaviour of the quiet-time daily field variations are in agreement with those of earlier studies for a mid-latitude observatory placed at the south of the southern hemisphere current focus. We also found a clear dependence of the Sq amplitude on solar activity, although the Sq amplitude maximum occurs about 2 years later than the sunspot maximum. An analysis of contemporary data for solar cycle 23 was carried out for observatories located in the same longitudinal sector, with the aim of identifying the latitudinal displacements of the current focus that affect the observed Sq variations. This was also determined for solar cycle 20 using data from a different set of observatories. The uncertainties associated with the method employed for determining the focus positions are due to the scarcity of observatory data in the South American-Antarctic Peninsula region, but based on our analysis, we can state with a certain reliability that focus latitudes are higher during the summer and at equinoxes than during the winter. However, it is difficult to establish a correlation between focus latitudes and solar sunspot numbers.