Sunspot Counts Research Articles

Understanding Solar Activity after the Maunder Minimum: Sunspot Records by Rost and Alischer

The Maunder Minimum was a period with significantly reduced solar activity between 1645 and 1715, approximately. The transition between the low solar activity in the Maunder Minimum and the subsequent “normal” regime of solar activity was gradual. However, there are discrepancies in the solar activity level from sunspot number indices and solar activity proxies in that period. Among the contemporaneous observers, Johann L. Rost and Sebastian Alischer were two key sunspot observers to understand the solar activity in this transition just after the Maunder Minimum. We have revised all their sunspot records, counting the number of groups and individual sunspots to derive reliable data for the solar activity level for the period 1716–1726. We found significant misinterpretations of the sunspot group counting assigned to these astronomers in the existing group number databases. Our new group sunspot counting significantly reduces the number of groups for Rost and Alischer’s observations compared to entries in existing databases. Furthermore, our sunspot number estimates (obtained from the active day fraction methodology) of the maximum amplitude of Solar Cycles −3 and −4 are significantly lower than the amplitudes according to the official sunspot number, but they are compatible with sunspot number values obtained from solar activity proxies such as radioisotopes. Our result would imply that solar activity after the Maunder Minimum recovered more gradually and with a lower intensity than previously considered.

Karl von Lindener’s sunspot observations during 1800–1827: Another long-term dataset for the Dalton Minimum

On a centennial timescale, solar activity oscillates quasi-periodically and also tends to occasionally get into a low-activity period. The Dalton Minimum (circa 1790s–1820s) was one of such low-activity periods that had been captured in telescopic sunspot observations. However, it has been challenging to analyse the Dalton Minimum, as contemporary source records remained mostly unpublished and almost inaccessible to the scientific community. Recent studies have established reliable datasets for sunspot group number, sunspot number, and sunspot positions. This study further analyzes independent Silesian sunspot observations from 1800 to 1827 in a manuscript from the Library of Wrocław University (Ms AKC.1985/15) and complements it with the metadata for the observer: Karl Christian Reinhold von Lindener. We identified 547 days of sunspot observations in these records and derived the sunspot group number, individual sunspot number, and sunspot positions between 1800 and 1827. The results of this study have significantly revised von Lindener’s sunspot group number, which was previously known for only 517 days in scientific databases, and removed contamination from general descriptions. Using our results, we extended investigations into individual sunspot counts and derived their positions. In our analysis, we locate von Lindener’s sunspot positions in both solar hemispheres and contrast the Dalton Minimum with the Maunder Minimum, adding further independent credits to the previous results for Derfflinger’s and Prantner’s datasets. Sunspot positions are also slightly biased towards the northern solar hemisphere in early Solar Cycle 6 (1812–1813). The high-latitude sunspot positions indicate the onset of Solar Cycle 7 as early as June 1822.

Automated Sunspot Detection as an Alternative to Visual Observations

We developed an automated method for sunspot detection using digital white-light solar images to achieve a performance similar to that of visual drawing observations in sunspot counting. To identify down to small, isolated spots correctly, we pay special attention to the accurate derivation of the quiet-disk component of the Sun, which is used as a reference to identify sunspots using a threshold. This threshold is determined using an adaptive method to process images obtained under various conditions. To eliminate the seeing effect, our method can process multiple images taken within a short time. We applied the developed method to digital images captured at three sites and compared the detection results with those of visual observations. We conclude that the proposed sunspot detection method has a similar performance to that of visual observation. This method can be widely used by public observatories and amateurs as well as professional observatories as an alternative to hand-drawn visual observation for sunspot counting.

Did Schwabe cycles 19–24 influence the ENSO events, PDO, and AMO indexes in the Pacific and Atlantic Oceans?

The sea surface temperature (SST), anomalies (SSTA), Oceanic Niño Index (ONI), and Multivariate ENSO (MEI) index in El Niño 1 + 2 and El Niño 3.4 regions, Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO), as well as the meteorological parameter Southern Oscillation Index (SOI) were cross correlated to sunspot counts (SS) from cycles 19 to 24 (1954–2019). Over the 1954–2019 period, the SS or Schwabe cycles did not show strong cross-correlation coefficients (cc-ρ) with values falling between 0.063 and 0.100 ( p < 0.05). It seems that the Total Solar Irradiation (TSI) constant variability (±0.1%, ±1.361 W m −2 ) due to the SS cycles balanced out throughout the whole period. The cc-ρ coefficients for SST and SSTA versus each individual SS cycles were between 0.100 and 0.200 with lag times between maxima of each being from a few to 48 months. The ONI showed a cc-ρ < 0.1, while MEI reached up to 0.2 through all SS cycles. The slope of the cc-ρ changed from negative to positive over 6–12 months periods, with peaks in slope change occurring somewhere between 2 and 3 years. The SOI cc-ρ varied by around 0.200 through cycles 19–21, but for SS 22–24 it was not noticeable. Interdecadal indexes PDO and AMO showed cc-ρ of up to 0.283; with a possible association of 8%, with a lag time of 1–3 years. During the ascending and descending phases of each SS cycle, the cc-ρ were 0.288 and − 0.233, respectively for SST in El Niño 3.4 region, but in El Niño 1 + 2 were negligible. The ONI and MEI showed cc-ρ up to 0.448 and 0.480 respectively with lag times of 1–15 months in ascending phase of the SS cycle. The SS vs SOI had cc- ρ up to +0.420 to −0.567 in the ascending phases, while PDO and AMO registered cc-ρ up to 0.417 and − 0.491. AMO appeared systematically associated with SS cycles from 10.0 to 30.2% during descending and ascending phases, respectively. Compiled SS counts for all the ascending and descending phases of the SS cycles, gave a clear spectral coherence (quasi sine-function distribution); for SST and SSTA, lag times of 9–48 months were observed with inverse and direct linear relationship, and peaks of −0.38 and 0.39, respectively. The ONI and MEI with SS counts have similar cc-ρ values: 0.245 and 0.387. Around 6–15% of the ONI and MEI can be explained by SS during ascending and < 4% in descending phases. It seems that over the relatively short time scales of SS cycles, either on their initial ascending or final descending phases, the studied indexes seem to be influenced. Even though it was difficult to elucidate the physics behind the observed cross-correlations, these results can be used to help improve understanding and aid the predictions of ENSO, PDO and AMO oceanographic events in the Pacific and Atlantic oceans. • Sea surface temperature is affected by sun energy that varies in time due to astronomical factors and sun internal activity • The sun activity can be estimated by sun spots (SS) • Inter-annual El/La Niño/Niña as well as decadal processes should be affected by SS • It was found weak to moderate cross-correlation between SS and oceanographic indexes from 1954 to 2019 • This fact should be considered to improve skill modelling forecasts of such indexes

Relationship between the Sunspot Number and Active Day Fraction: An Application for the Maunder Minimum

Long-term solar activity can be studied using several parameters. Some of the most used are based on the sunspot counting. The active day fraction (ADF) is the simplest index derived from this counting. It is reliable in periods of low solar activity such as the Maunder minimum (MM). In this work, we study the relationship between the ADF and the sunspot number. We have obtained that the optimal fit of that relationship is an exponential function whose exponent is a degree 3 polynomial including all data except those with ADF equal to 100%. Then, we use that fit to estimate the sunspot number during the MM from the ADF calculated from the most recent sunspot group number database. Our estimations of the annual sunspot numbers are below 15, except that for 1656, which is 40.8, whereas our estimations of the triennial sunspot numbers are below 10 from 1648 to 1714. We have found peaks of the solar cycle in the middle of the 1650s, 1670s, 1680s, and 1700s but no clear evidence of solar cycle in the 1660s and 1690s, likely due to the scarcity of the available data. Our results agree with previous works obtaining values significantly higher than those of the group sunspot number derived by Hoyt and Schatten in 1998 but still fully compatible with a grand minimum period.

Aerosol Populations, Processes, and Ages in Bulk Deposition: Insights From a 9‐Year Study of 7Be, 210Pb, Sulfate, and Major/Trace Elements

AbstractWe report fallout radionuclide (FRN) and major/trace element (MTE) contributions to bulk atmospheric deposition in Hanover, NH, USA (43.7022°N, 72.2896°W). Deposition of 7Be, 210Pb, and SO4 covary [R2 &gt; 0.4, n = 461] but are discriminated by production sources, depositional mechanisms, meteorological controls, MTE associations, and seasonal biases. 7Be is dominated by rainout (78% of total deposition), recharged by long‐range transport (+23% over mean, o.m.), influenced by stratosphere‐troposphere exchange (+9% o.m.), and solar activity (−2% per doubling of sunspot count). Correlation with particulate nitrogen (+9% per doubling of N) indicates 7Be affinity for biogenic aerosols. 210Pb is dominated by dry + washout deposition (54% of total) and convective storms (+107% o.m), depleted in marine moisture sources (−133% o.m.), correlated with S (+9% per doubling of S), and biased to autumn with Mn, Hg, and V (+7% o.m.). Coincident long‐term declines in S and 210Pb (−14%, −4% per year) suggest co‐scavenging by PbSO4. 7Be:210Pb ratios increase asymptotically with precipitation through the dry‐washout‐rainout transition and recharge of 7Be. At the global scale, 7Be:210Pb increases with precipitation for North American/European sites due to recharge of 7Be in midlatitude storm belts [R2 = 0.64, n = 31]. Conversely, 7Be:210Pb is independent of precipitation for Southeast/East Asian sites where 7Be recharge is low [R2 = 0.01, n = 40]. Globally, 7Be:210Pb ratios in dry deposition reflect resuspended aerosols with mean age of ca. 200 days, contributing &lt;5% of 210Pb deposition. Different aerosol populations contributing to FRN deposition across spatial and temporal scales should emerge as a focus in terrestrial 7Be, 210Pb, and 10Be tracer applications.

Reconstruction of the Sunspot Number Source Database and the 1947 Zurich Discontinuity

The recalibration of the sunspot number series, the primary long-term record of the solar cycle, requires the recovery of the entire collection of raw sunspot counts collected by the Zurich Observatory for the production of this index between 1849 and 1980.Here, we report about the major progresses accomplished recently in the construction of this global digital sunspot number database, and we derive global statistics of all the individual observers and professional observatories who provided sunspot data over more than 130 years.First, we can announce the full recovery of long-lost source-data tables covering the last 34 years between 1945 and 1979, and we describe the unique information available in those tables. We then also retrace the evolution of the core observing team in Zurich and of the auxiliary stations. In 1947, we find a major disruption in the composition of both the Zurich team and the international network of auxiliary stations.This sharp transition is unique in the history of the Zurich Observatory and coincides with the main scale-jump found in the original Zurich sunspot number series, the so-called “Waldmeier” jump. This adds key historical evidence explaining why methodological changes introduced progressively in the early 20th century could play a role precisely at that time. We conclude on the remaining steps needed to fully complete this new sunspot data resource.

Is the primary CoRoT target HD 43587 under a Maunder minimum phase?

Context. One of the most enigmatic phenomena related to solar activity is the so-called Maunder minimum phase. It consists in the lowest sunspot count ever registered for the Sun and has not been confirmed for other stars to date. Since the spectroscopic observations of stellar activity at the Mount Wilson Observatory, the solar analog HD 43587 has shown a very low and apparently invariant activity level, which makes it a Maunder minimum candidate. Aims. We aim to analyze the chromospheric activity evolution of HD 43587 and its evolutive status, with the intention of unraveling the reasons for this low and flat activity. Methods. We used an activity measurements dataset available in the literature, and computed the S-index from HARPS and NARVAL spectra to infer a cycle period. Additionally, we analyzed the CoRoT light curve of HD 43587, and applied gyrochronology and activity calibrations to determine its rotation period. Finally, based on an evolutionary model and the inferred rotation period, we used the EULAG-MHD code to perform global MHD simulations of HD 43587 to get some insight into its dynamo process. Results. We confirm the almost flat activity profile, with a cycle period Pcyc = 10.44 ± 3.03 yr deduced from the S-index time series, and a long-term trend that might be a period of more than 50 yr. It was impossible to define a rotation period from the light curve, however gyrochronology and activity calibrations allow us to infer an indirect estimate of ¯Prot = 22.6 ± 1.9 d. Furthermore, the MHD simulations confirm an oscillatory dynamo with a cycle period in good agreement with the observations and a low level of surface magnetic activity. Conclusions. We conclude that this object might be experiencing a “natural” decrease in magnetic activity as a consequence of its age. Nevertheless, the possibility that HD 43587 is in a Maunder minimum phase cannot be ruled out.

Transfer learning in spatial–temporal forecasting of the solar magnetic field

AbstractMachine learning techniques have been widely used in attempts to forecast several solar datasets such as the sunspot count, the sunspot area, flare activity, solar wind magnitude, and solar storms/coronal mass ejections (CMEs) activity. Most of these approaches employ supervised machine learning algorithms which are, in general, very data hungry. This hampers the attempts to forecast some of these data series, particularly the ones that depend on (relatively) recent space observations such as those obtained by the Solar and Heliospheric Observatory and the Solar Dynamics Observatory. Here we focus on an attempt to forecast the solar surface longitudinally averaged unsigned radial component (or line‐of‐sight) magnetic field distribution using a form of spatial–temporal neural networks. Given that the recording of these spatial–temporal datasets only started in 1975 and are therefore quite short, the forecasts are predictably quite modest. However, given that there is a potential physical relationship between sunspots and the magnetic field, we employ another machine learning technique called transfer learning which has recently received considerable attention in the literature. Here, this approach consists in first training the source spatial–temporal neural network on the much longer time/latitude sunspot area dataset, which starts in 1874, then transferring the trained set of layers to a target network, and continue training the latter on the magnetic field dataset. The employment of transfer learning in the field of computer vision is known to obtain a generalized set of feature filters that can be reused for other datasets and tasks. Here we obtain a similar result, whereby we first train the network on the spatial–temporal sunspot area data, then the first few layers of the neural network are able to identify the two main features of the solar cycle, that is, the amplitude variation and the migration to the equator, and therefore can be used to train on the magnetic field dataset and forecast better than a prediction based only on the historical magnetic field data.

Sunspot Positions and Areas from Observations by Thomas Harriot

The reconstruction of sunspot parameters in the early era of telescopic observations extends our knowledge on visual sunspot activity up to 400 years into the past. 200 digital solar images from 18 December 1610 to 28 January 1613 by the English astronomer Thomas Harriot were analyzed to yield sunspot counts, areas and positions. Harriot generally observed in the early morning when the Sun was near the horizon, and he specified the local time of observation, date, place, number of spots, zenith and ecliptic lines, and other information. We assigned 753 sunspots into 293 groups and defined their areas. We developed two approaches to reconstructing the heliographic coordinates of the sunspots. Method I makes use of the time of observation noted by Harriot, and Method II minimizes the day-to-day variability of sunspot latitudes independently of Harriot’s notes. The results of the two methods are discussed.

Effect of a magnetic pulse on orientation behavior in rainbow trout (Oncorhynchus mykiss)

Magnetoreception remains one of the most enigmatic of animal senses. Rainbow trout (Oncorhynchus mykiss) represent an ideal species to study this sense, as magnetoreception based upon microscopic particles of magnetite is suspected to play an important role in their orientation and navigation. Here we found that compared with controls, a magnetic pulse (a treatment commonly used to demonstrate magnetite-based magnetoreception) can induce orientation behavior in juvenile rainbow trout on a specific experimental day. Multiple circular-linear regression also indicated that this effect could at least be partially explained by daily variation in solar electromagnetic activity (i.e., sunspot count and disturbance storm time index). These results are consistent with magnetite-based magnetoreception in rainbow trout and suggest that 1) solar activity may impact magnetic orientation and 2) researchers should be cognizant of its potential consequences on studies of magnetoreception.

Uncertainty Quantification in Sunspot Counts

Abstract Observing and counting sunspots constitutes one of the longest-running scientific experiments, with first observations dating back to Galileo (around 1610). Today the sunspot number (SN) time series acts as a benchmark of solar activity in a large range of physical models. An appropriate statistical modeling, adapted to the time series’ complex nature, is, however, still lacking. In this work, we provide the first comprehensive uncertainty quantification analysis of sunspot counts. We study three components: the number of sunspots (N s ), the number of sunspot groups (N g ), and the composite N c , defined as . Those are reported by a network of observatories around the world and are corrupted by errors of various types. We use a multiplicative framework to provide, for these three components, an estimation of their error distribution in various regimes (short-term, long-term, minima of solar activity). We also propose a robust estimator for the underlying solar signal and fit density distributions that take into account intrinsic characteristics such as overdispersion, excess of zeros, and multiple modes. The estimation of the solar signal underlying the composite N c may be seen as a robust version of the International Sunspot Number (ISN), widely used as a proxy of solar activity. Therefore, our results on N c may help characterize the uncertainty on ISN as well. Our results pave the way for a future monitoring of the observatories in quasi-real time, with the aim of alerting the observers when they start deviating from the network and preventing large drifts from occurring.

The effect of telescope aperture, scattered light and human vision on early measurements of sunspot and group numbers

ABSTRACT Early telescopic observations of sunspots were conducted with instruments of relatively small aperture. These instruments also suffered from a higher level of scattered light, and the human eye served as a ‘detector’. The eye’s ability to resolve small details depends on image contrast, and on average intensity variations smaller than ≈3 per cent contrast relative to background are not detected even if they are resolved by the telescope. Here we study the effect of these three parameters (telescope aperture, scattered light and detection threshold of human vision) on sunspot number, group number and area of sunspots. As an ‘ideal’ dataset, we employ white-light (pseudo-continuum) observations from the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory, and we model the appearance of sunspots by degrading the HMI images to corresponding telescope apertures with added scattered light. We discuss the effects of different parameters on sunspot counts and derive functional dependences, which could be used to normalize historical observations of sunspot counts to a common denominator.

Information dynamics with confidence: Using reservoir computing to construct confidence intervals for information-dynamic measures.

Information dynamics provides a broad set of measures for characterizing how a dynamical system stores, processes, and transmits information. While estimators for these measures are commonly used in applications, the statistical properties of these estimators for finite time series are not well understood. In particular, the precision of a given estimate is generally unknown. We develop confidence intervals for generic information-dynamic parameters using a bootstrap procedure. The bootstrap procedure uses an echo state network, a particular instance of a reservoir computer, as a simulator to generate bootstrap samples from a given time series. We perform a Monte Carlo analysis to investigate the performance of the bootstrap confidence intervals in terms of their coverage and expected lengths with two model systems and compare their performance to a simulator based on the random analog predictor. We find that our bootstrap procedure generates confidence intervals with nominal, or near nominal, coverage of the information-dynamic measures, with smaller expected length than the random analog predictor-based confidence intervals. Finally, we demonstrate the applicability of the confidence intervals for characterizing the information dynamics of a time series of sunspot counts.

Sunspot observations by Charles Malapert during the period 1618–1626: a key data set to understand solar activity before the Maunder minimum

ABSTRACT A revision is presented of the sunspot observations made by Charles Malapert from 1618 to 1626, studying several documentary sources that include those observations. The revised accounting of the group numbers recorded by Malapert for that period shows new information unavailable in the current sunspot group data base. The average solar activity level calculated from these revised records of Malapert is by almost one-third greater than that calculated from his records included in the current group data base. Comparison of the sunspot observations made by Malapert and by other astronomers of that time with regard to the number of recorded groups and sunspot positions on the solar disc shows good agreement. Malapert reported that he only recorded one sunspot group in each sunspot drawing presented in Austriaca Sidera Heliocyclia (the documentary source that includes most of the sunspot records made by Malapert), although he sometimes observed several groups. Therefore, the sunspot counts obtained in this work on Malapert's sunspot observations represent the lower limit of the solar activity level corresponding to those records.

Sunspot Observations Made by Hallaschka During the Dalton Minimum

We present and analyse the sunspot observations performed by Franz I. C. Hallaschka in 1814 and 1816. These solar observations were carried out during the so-called Dalton minimum, around the maximum phase of the Solar Cycle 6. These records are very valuable because they allow us to complete observational gaps in the collection of sunspot group numbers, improving its coverage for this epoch. We have analysed and compared the observations made by Hallaschka with the records made by other contemporary observers. Unfortunately, the analysis of the sunspot areas and positions showed that they are too inaccurate for scientific use. But, we conclude that sunspot counts made by Hallaschka are similar to those made by other astronomers of that time. The observations by Hallaschka confirm a low level of the solar activity during the Dalton minimum.

Temporal and Periodic Variations of Sunspot Counts in Flaring and Non-Flaring Active Regions

We analyzed temporal and periodic behavior of sunspot counts (SSCs) in flaring (C, M, or X class flares), and non-flaring active regions (ARs) for the almost two solar cycles (1996 through 2016). Our main findings are as follows: i) The temporal variation of monthly means of daily total SSCs in flaring and non-flaring ARs are different and these differences are also varying from cycle to cycle; temporal profile of non-flaring ARs are wider than the flaring ones during the solar cycle 23, while they are almost the same during the current cycle 24. The second peak (second maximum) of flaring ARs are strongly dominate during current cycle 24, while this difference is not such a remarkable during cycle 23. The amplitude of SSCs in the non-flaring ARs are comparable during the first and second peaks (maxima) of the current solar cycle, while the first peak is almost not existent in case of the flaring ARs. ii) Periodic variations observed in SSCs of flaring and non-flaring ARs are quite different in both MTM spectrum and wavelet scalograms and these variations are also different from one cycle to another; the largest detected period in the flaring ARs is 113 days, while there are much higher periodicities (327, 312, and 256 days) in non-flaring ARs. There are no meaningful periodicities in MTM spectrum of flaring ARs exceeding 45 days during solar cycle 24, while a 113 days periodicity detected from flaring ARs of solar cycle 23. For the non-flaring ARs the largest period is 72 days during solar cycle 24, while the largest period is 327 days during current cycle.

The Effect of Sunspot Weighting

Although W. Brunner began to weight sunspot counts (from 1926), using a method whereby larger spots were counted more than once, he compensated for the weighting by not counting enough smaller spots in order to maintain the same reduction factor (0.6) as was used by his predecessor A. Wolfer to reduce the count to R. Wolf’s original scale, so that the weighting did not have any effect on the scale of the sunspot number. In 1947, M. Waldmeier formalized the weighting (on a scale from 1 to 5) of the sunspot count made at Zurich and its auxiliary station Locarno. This explicit counting method, when followed, inflates the relative sunspot number over that which corresponds to the scale set by Wolfer (and matched by Brunner). Recounting some 60,000 sunspots on drawings from the reference station Locarno shows that the number of sunspots reported was “over counted” by \({\approx}\,44~\%\) on average, leading to an inflation (measured by an effective weight factor) in excess of 1.2 for high solar activity. In a double-blind parallel counting by the Locarno observer M. Cagnotti, we determined that Svalgaard’s count closely matches that of Cagnotti, allowing us to determine from direct observation the daily weight factor for spots since 2003 (and sporadically before). The effective total inflation turns out to have two sources: a major one (15 – 18 %) caused by weighting of spots, and a minor source (4 – 5 %) caused by the introduction of the Zurich classification of sunspot groups which increases the group count by 7 – 8 % and the relative sunspot number by about half that. We find that a simple empirical equation (depending on the activity level) fits the observed factors well, and use that fit to estimate the weighting inflation factor for each month back to the introduction of effective inflation in 1947 and thus to be able to correct for the over-counts and to reduce sunspot counting to the Wolfer method in use from 1894 onwards.

Possible variations in sunspot groups before flaring activity during solar cycles \\ 23 and 24

We investigated the possible morphological variations observed in sunspot groups on the day before flaring activity occurred between January 1996 and November 2014. We found that 77% of all flaring sunspot groups were large and complex (D, E, and F modified Zurich classes). In addition, the Zurich classification of A, B, and C class sunspot groups changed more than 50%, while the remaining groups (D, E, F, and H) did not change considerably before the flare activity. Results showed that there was a remarkable increase in the sunspot areas of groups D, E, and F; in contrast, the sunspot areas of groups A, B, C, and H showed a decrease before the flaring activity during the examined time period. Finally, the sunspot counts of groups A, C, and H showed a decrease, while groups B, D, E, and F showed an increase in the same period.

Temporal variations of different solar activity indices through the solar cycles 21-23

Here, we compare the sunspot counts and the number of sunspot groups (SGs) with variations of total solar irradiance (TSI), magnetic activity, Ca II K-flux, faculae and plage areas. We applied a time series method for extracting the data over the descending phases of solar activity cycles (SACs) 21, 22 and 23, and the ascending phases 22 and 23. Our results suggest that there is a strong correlation between solar activity indices and the changes in small (A, B, C and H-modified Zurich Classification) and large (D, E and F) SGs. This somewhat unexpected finding suggests that plage regions substantially decreased in spite of the higher number of large SGs in SAC 23 while the Ca II K-flux did not decrease by a large amount nor was it comparable with SAC 22 and relates with C and DEF type SGs. In addition to this, the increase of facular areas which are influenced by large SGs, caused a small percentage decrease in TSI while the decrement of plage areas triggered a higher decrease in the magnetic field flux. Our results thus reveal the potential of such a detailed comparison of the SG analysis with solar activity indices for better understanding and predicting future trends in the SACs.