The study, published in the journal Solar Physics, was led by Partha Chowdhury of the University of Calcutta together with Jagdev Singh, V. Muthu Priyal, and Belur Ravindra of the Indian Institute of Astrophysics in Bengaluru. The researchers analyzed digitized images taken in the light of singly ionized calcium, the Ca ii K spectral line, from the Kodaikanal Solar Observatory. These images capture the chromosphere, a thin layer of the solar atmosphere sitting just above the visible photosphere, where magnetic fields heat the gas and make bright regions known as plages blaze in ultraviolet-adjacent wavelengths. Plages are the chromospheric ghosts of sunspots: where magnetic flux crowds the surface, the calcium emission brightens, even when no dark spot is present.

Because plages are visible even when sunspots are not, they offer a more complete census of the Sun’s magnetic activity than sunspot counts alone. The Kodaikanal archive, spanning Solar Cycles 14 through 22, roughly the first nine decades of the twentieth century, is one of the longest continuous records of chromospheric behavior anywhere in the world. After careful digitization and homogenization, a process that corrects for changes in photographic plates, instruments, and observing conditions over the decades, the team measured the total area covered by plages on every available day and compared it with three standard yardsticks of solar activity: the international sunspot number, the total sunspot area, and the 10.7 centimeter radio flux, a microwave emission that tracks coronal magnetic heating.

The correlations the team found are strikingly strong. Across all nine cycles, the chromospheric plage area tracks each of the photospheric and coronal activity indices with correlation coefficients exceeding 0.85, a level of agreement that leaves little doubt that the Sun’s upper and lower atmospheric layers are driven by the same underlying magnetic engine. This matters for more than just bookkeeping. Because plage records extend further back in time than some modern instruments, they can serve as a reliable proxy for reconstructing solar activity across the twentieth century, including the ultraviolet output that subtly influences Earth’s upper atmosphere and climate system.

But the study went beyond simple correlations. The researchers examined whether the plage areas obey two well-known but poorly understood features of the solar cycle. The first is the Gnevyshev-Ohl rule, an empirical oddity noting that in most pairs of consecutive solar cycles, the odd-numbered cycle is stronger than the even-numbered one that precedes it. The team confirmed that plage areas follow this rule, suggesting that the chromosphere inherits the same cycle-to-cycle memory that governs sunspot production. The second feature is the Gnevyshev gap, a temporary dip in activity that often splits the peak of a solar cycle into two humps. The analysis revealed clear Gnevyshev gaps in the plage data during several cycle maxima, confirming that this double-peaked structure is not merely a sunspot quirk but a genuine, whole-Sun phenomenon imprinted on the chromosphere as well.

To dig deeper into the timing of these variations, the team turned to a powerful mathematical technique called Morlet wavelet analysis, which can detect oscillations whose strength and period change over time, something a traditional Fourier analysis cannot do. They supplemented this with wavelet coherence, a method that measures not just whether two signals share a rhythm, but whether those rhythms stay in step with each other, drifting in and out of phase like two musicians who occasionally lose the beat. The technique is widely used in geophysics and climate science, and it is ideally suited to the Sun, whose magnetic activity is famously irregular.

The wavelet analysis uncovered two families of intermediate-term periodicities hiding inside the dominant eleven-year cycle. The first are Rieger-type periods, oscillations of roughly 130 to 190 days. These were first discovered in 1984, when researchers noticed that gamma-ray flares from the Sun seemed to cluster with a period of about 154 days. Since then, similar periodicities have been found in sunspots, flares, and coronal mass ejections, and they are widely interpreted as the signature of magnetic Rossby waves, vast, planet-scale waves of magnetized plasma rolling around the Sun’s interior shear layer known as the tachocline, where the Sun’s differential rotation winds up its magnetic field. The second family comprises quasi-biennial oscillations, or QBOs, with periods of one to four years, which are thought to reflect a secondary magnetic cycle operating in parallel with the main eleven-year one.

Here the story takes an intriguing turn. The Rieger-type periods and QBOs show considerable variability from one solar cycle to the next, and the wavelet coherence analysis reveals that at these intermediate timescales, the chromospheric plage areas and the photospheric activity indices frequently fall out of phase with one another. The rhythms exist, but they do not always march together. This asynchrony suggests that the shorter-period variations may arise from processes that affect the chromosphere and photosphere differently, or from instabilities in the tachocline whose surface manifestations depend on the details of each individual cycle, including the strength of the interior magnetic field at the time.

At the fundamental scale, however, the picture is one of remarkable unity. Within the 9 to 12 year periodicity belt that defines the solar cycle itself, the team found a stable phase synchrony between chromospheric plages and every photospheric and coronal index they examined. In other words, over the long haul, the Sun’s chromosphere and its visible surface rise and fall together like two ends of the same magnetic tide. This tight decadal coupling is exactly what modern solar dynamo models predict: magnetic fields generated by the rotation of plasma at the tachocline buoyantly rise through the convection zone, emerge as sunspots and active regions in the photosphere, and simultaneously light up the overlying chromosphere as plages. The new results provide hard empirical constraints that any credible dynamo model must now reproduce.

The findings also align with theoretical work on tachocline instabilities and magnetic Rossby waves, which have been invoked to explain everything from the double-peaked shape of solar maxima to the so-called seasons of space weather, bursts of intense flaring that come and go over months. By confirming Rieger-type and quasi-biennial signals in a chromospheric dataset spanning nine cycles, the study strengthens the case that these waves are a persistent feature of the solar interior rather than a fluke of a few well-observed cycles. For space weather forecasters, the implications are tantalizing: if the phase relationships between these periodicities and the activity indices can be pinned down well enough, the hidden rhythms of the tachocline might one day help anticipate the timing of the most active and hazardous phases of the solar cycle. For now, the century-old glass plates of Kodaikanal have once again proven that some of the best windows into the Sun’s deepest secrets were captured long before the space age began.

Subject of Research: Long-term chromospheric plage evolution and its relationship to solar activity indices across Solar Cycles 14 to 22

Article Title: Long-term Evolution of Chromospheric Plage Areas from Kodaikanal Observatory Ca ii K Images and Their Relation to Solar Activity Indices

Article References: Chowdhury, P., Singh, J., Priyal, V. M., & Ravindra, B. (2026). Long-term Evolution of Chromospheric Plage Areas from Kodaikanal Observatory Ca ii K Images and Their Relation to Solar Activity Indices. Solar Physics, 301(10), Article 149. https://doi.org/10.1007/s11207-026-02733-y

Image Credits: AI Generated

DOI: 10.1007/s11207-026-02733-y

Keywords: solar physics, chromosphere, Ca ii K, solar plages, solar cycle, sunspots, Rieger periodicity, quasi-biennial oscillations, solar dynamo, tachocline, Rossby waves, Kodaikanal Observatory

The tale at the centre of the investigation is a striking one. The first practical electric telegraph networks were deployed during the 1840s, and as solar activity rose in the years that followed, Victorian telegraph operators began to experience strange and unexplained electrical effects caused by geomagnetic disturbances. According to the original account, the 10:05 p.m. train departing Exeter in Devon was delayed by 16 minutes when a very intense magnetic disturbance interfered with the electric signalling telegraph equipment used to determine whether the railway line ahead was clear. Without a working telegraph link, the signalman could not confirm that the track was unoccupied, and the train was held until the disturbance subsided. It is a vivid illustration of solar activity reaching down into everyday Victorian life through the copper wires of a young technology.

Professor Jim Wild of Lancaster University’s School of Physics and Astronomy, the lead author of the study, worked with scientists from the British Geological Survey, Natural Resources Canada, Baylor University, RMIT University and STFC RAL Space to test whether the account could withstand modern scrutiny. The team encountered a critical problem almost immediately: the railway line referenced in the story did not open until 1846, almost five years after the alleged 1841 incident. A train could not have been delayed on a line that did not yet exist. That single discrepancy opened the door to a broader re-examination of the event, and suggested that the date recorded in the 1871 Nature article might simply have been a typographical error, with 1848 misprinted as 1841.

To establish what really happened, the researchers assembled an unusually rich body of evidence, combining railway timetables, historical newspaper reports, solar observations, auroral accounts and digitised geomagnetic records. Their investigation identified a strong geomagnetic disturbance on 18 October 1848, exactly the kind of event that would have disrupted telegraph signalling. Crucially, the same date is accompanied by reports of sunspots and aurora seen across the United Kingdom and continental Europe, an independent signature of heightened solar and geomagnetic activity. Taken together, the evidence provides compelling support for the conclusion that the Exeter delay occurred in 1848, and that the earlier date was a clerical slip that propagated through the scientific literature for 178 years.

The correction changes the historical record in an important way. While the Exeter incident remains one of the earliest documented examples of space weather disrupting technology, it was not the first. The earliest credible report currently known is interference with telegraph systems on the Midland Railway in March 1847. That distinction shifts the timeline of humanity’s first encounter with the space environment back to the earliest years of the electric telegraph, and it demonstrates how quickly engineers of the 1840s began to notice that their new networks were sensitive to forces they could not yet explain. Geomagnetic disturbances induce currents in long conductors, and telegraph lines stretching across the countryside were effectively enormous antennas that picked up the electrical signature of a restless magnetosphere.

Professor Wild reflected on the significance of the finding for how society understands the hazard. Space weather is often discussed as a modern challenge because of contemporary dependence on satellites, communications systems and electricity networks, yet the study shows that society has been experiencing the effects of space weather on technology for almost as long as electrical technologies have existed. The Exeter train delay, he noted, is a fascinating story because it sits right at the point where emerging technologies first began to encounter the realities of the space environment. By combining historical archives with scientific observations, the team was able to show that the event almost certainly happened in 1848 rather than 1841, and although this means it is not the earliest recorded space weather impact, it remains one of the first clear examples of solar activity disrupting critical infrastructure.

The research also carries a methodological lesson that extends well beyond railway history. Dr Mike Hapgood, Visiting Scientist and space weather expert at STFC’s RAL Space, described the work as having a hint of a detective story, piecing together a wide range of archived records to better understand a historically severe space weather event. He emphasised the importance of preserving older records, which give scientists the evidence base they need to interpret past events and strengthen future predictions. Digitised geomagnetic measurements, newspaper archives and railway timetables proved to be complementary strands of evidence, and their combination allowed the team to date a geomagnetic storm with a precision that no single source could have provided. For researchers reconstructing the history of solar activity, the study is a demonstration of how much information still lies waiting in nineteenth-century archives.

The physical mechanism behind the Exeter delay is well understood today. When the Sun ejects clouds of magnetised plasma toward Earth, the resulting shock compresses the planet’s magnetic field and drives rapidly varying electric currents in the ionosphere. Those variations, in turn, induce voltages in long conductors on the ground, a phenomenon now known as a geomagnetically induced current. In the 1840s these currents manifested as spurious signals, erratic needle deflections and intermittent failures on telegraph circuits, sometimes strong enough to disrupt railway signalling entirely. The same physics operates today, but the conductors are high-voltage transmission lines, pipeline networks and the grounding systems of power transformers, and the consequences of a severe storm can range from GPS errors to regional blackouts.

Nearly two centuries after the Exeter delay, railways and other critical infrastructure remain vulnerable to space weather, although through very different technologies including power systems, signalling equipment, satellite navigation and communications networks. Professor Wild observed that the research highlights space weather as not a new threat but a long-standing natural hazard. The technologies affected have evolved from railway telegraphs to satellites, communications networks and power systems, but the challenge remains the same: understanding the risk and ensuring society is resilient to its impacts. The continuity is striking, since a signalman waiting for a telegraph needle to settle in 1848 and a grid operator monitoring geomagnetic indices today are responding to the same solar-driven disturbance in Earth’s magnetic environment.

Dr Hapgood added a note of caution about the future. While today’s space weather capabilities are far more advanced than anything available in the 1800s, the modern technologies society depends on are also much more vulnerable to solar storms. Deepening the understanding of these events, he argued, is essential for preparing for and mitigating the impacts of space weather, especially as the world looks forward to a decade of ambitious space developments that will face the challenge of a new solar cycle in the 2030s. The Exeter story, corrected at last, thus serves a double purpose: it resets the historical record of humanity’s first technological encounter with the Sun’s outbursts, and it reminds a technology-dependent civilisation that the hazard has never gone away, only changed its address.

Subject of Research: Historical reconstruction of an 1848 geomagnetic disturbance that delayed a train in Exeter, correcting the date of one of the earliest recorded space weather impacts on technology

Article Title: Mystery of one of the earliest recorded space weather impacts solved

Article References: Mystery of one of the earliest recorded space weather impacts solved. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: space weather, geomagnetic storm, telegraph, Exeter, railway history, solar activity, aurora, sunspots, geomagnetically induced currents, Lancaster University, Space Weather journal, Victorian technology

Sunspot oscillations have fascinated solar physicists for more than half a century. Ever since chromospheric inhomogeneities in umbral regions were first reported in 1969, researchers have recognised that the magnetised plasma trapped within a sunspot does not sit still. Instead, it trembles with a superposition of waves, from the famous three-minute umbral oscillations to the five-minute oscillations that dominate the quiet solar photosphere. These waves are not mere curiosities. They are diagnostic tools, carrying information about the temperature, density and magnetic field structure of the solar atmosphere from the photosphere up through the chromosphere. Because the waves are shaped by magneto-acoustic mode conversion, absorption of acoustic p-modes and the geometry of magnetic flux tubes, measuring their periods precisely allows scientists to test models of magneto-convection and wave propagation in conditions that cannot be replicated in any laboratory on Earth.

What makes the new study distinctive is both the observational window and the analytical rigour. The 8 to 10 micrometre band occupies the thermal infrared, a regime in which the solar continuum emission is formed in well-understood layers of the photosphere and lower chromosphere, and in which the contrast between magnetic and non-magnetic plasma behaves differently than in visible light. The AIMS telescope, described in a 2025 overview of its trial observations, was designed to exploit precisely this window, combining infrared imaging with magnetic-field measurements from the high-altitude, thin-air environment of Lenghu in western China. Liu extracted light curves from three distinct regions of each sunspot observation: the dark umbra at the centre, the filamentary penumbra surrounding it, and the magnetically quiet Sun nearby, and then applied wavelet analysis, a mathematical technique well suited to detecting oscillatory signals whose strength varies over time.

The heart of the paper is a methodological comparison. Rather than trusting a single data-processing pipeline, Liu evaluated four distinct approaches for converting two-dimensional image sequences into oscillation measurements. Two of the methods perform wavelet analysis pixel by pixel across the field of view and then aggregate the resulting period information, either by taking the mean or the median across pixels. The other two first collapse the spatial information by computing either the mean or the median intensity across a region at each time step, and only then apply the wavelet transform to the resulting single time series. The distinction may sound technical, but it turns out to matter enormously, because spatial averaging before analysis can distort the very oscillation signal researchers are trying to measure.

The results are striking in their consistency. Across all six sunspot datasets, three of the four methods, namely pixel-wise wavelet analysis with mean aggregation, pixel-wise wavelet analysis with median aggregation, and spatial median aggregation before wavelet analysis, recovered the same period hierarchy with one hundred percent consistency: the umbra always shows the shortest periods, the penumbra intermediate ones, and the quiet Sun the longest. Typical weighted mean periods came out at roughly 260 to 313 seconds in the umbra, 286 to 374 seconds in the penumbra, and 294 to 382 seconds in the quiet Sun. In other words, the magnetically dominated heart of the sunspot rings fastest, while the surrounding plasma oscillates more slowly, a pattern that carries direct implications for how waves are generated and propagate through strongly magnetised regions of the solar surface.

The one method that fell short is revealing. Computing the spatial mean before the wavelet analysis achieved full consistency with the umbral-penumbral-quiet-Sun ordering in only one of the six datasets, partial consistency in three, and outright inconsistency in two, with the failures involving cases where the umbral period no longer came out as the shortest. The reason lies in a well-known pitfall of averaging: when a region contains spatially varying oscillation signals, taking the mean can suppress genuine oscillatory power and blend distinct modes into a misleading composite. The study quantifies this distortion precisely, showing that spatial smoothing generally increases the measured periods, by up to 21 percent, with the umbra showing the highest sensitivity to the effect. For observers planning future campaigns, the message is unambiguous: pixel-wise analysis with careful aggregation is the safer path.

Beyond the hierarchy of periods, the study addresses a deeper question about the physical character of solar oscillations. For each dataset, Liu computed the ratio of the power in secondary oscillation peaks to the power in the dominant peak. Every single ratio fell below 0.3, with a mean of 0.14 plus or minus 0.03. This is a strong quantitative confirmation that sunspot oscillations are inherently multi-mode phenomena rather than clean single-frequency signals. The dominant period, the one that stands tallest in a wavelet power spectrum, therefore tells only part of the story. Liu argues that the weighted mean period, which accounts for the distribution of power across modes, is physically more meaningful than the dominant period alone, better representing the true multi-mode nature of the oscillations that magnetised solar plasma supports.

These findings arrive at a moment when the solar physics community is investing heavily in new ground-based facilities capable of observing the Sun in underexplored spectral bands. The 8 to 10 micrometre window, the study concludes, deserves recognition as a valuable diagnostic for solar physics, complementing the visible and near-infrared channels on which most historical sunspot oscillation measurements have relied. The thermal infrared continuum in this band is sensitive to the temperature structure of the solar atmosphere, and its behaviour during energetic events such as flares has been modelled extensively, making it a natural arena for studying how magnetic structures modulate thermal emission on oscillation timescales. Establishing a robust baseline of oscillation properties in this band, across multiple sunspots and multiple analysis methods, provides the observational foundation that future theoretical work on magneto-convection and wave propagation will need.

The practical stakes extend beyond pure science. Sunspots are the seats of solar flares and coronal mass ejections, the eruptions that drive space weather and can disrupt satellites, radio communications and power grids on Earth. Oscillations within sunspots are thought to be linked to the dynamics of the magnetic fields that ultimately power these events, and some researchers have proposed that changes in oscillation behaviour could serve as precursors of eruptive activity. A reliable, reproducible method for measuring sunspot oscillation periods, validated across six independent datasets and four analytical pipelines, is a step toward making such monitoring quantitative. The study also carries a quiet tribute to observational perseverance: the acknowledgements credit the staff of the Huairou Solar Observing Station, whose engineers and observers worked under the extremely harsh conditions of high altitude and thin air at Lenghu to obtain the high-quality data on which the entire analysis rests.

For now, the immediate contribution is a set of firm numbers and a clear methodological verdict. The umbra of a sunspot oscillates with weighted mean periods of roughly 260 to 313 seconds, the penumbra at 286 to 374 seconds, and the quiet Sun at 294 to 382 seconds, and that ordering holds without exception when the data are handled correctly. Solar oscillations are genuinely multi-mode, with secondary peaks carrying a modest but real fraction of the total power. And the way astronomers average their data can shift the answer by a fifth of the measured period if they are careless. As AIMS and its successors accumulate more observing time in the thermal infrared, the Sun’s magnetic bells will keep ringing, and scientists will keep learning how to hear them with ever greater fidelity.

Subject of Research: Oscillation period properties of sunspots observed in the 8 to 10 micrometre infrared band

Article Title: Oscillation Period Properties of Sunspots in the 8 – 10 (\mu )m Infrared Band: A Multi-Dataset Analysis

Article References: Liu, S. (2026). Oscillation Period Properties of Sunspots in the 8 – 10 $\mu $m Infrared Band: A Multi-Dataset Analysis. Solar Physics, 301(9), Article 131. https://doi.org/10.1007/s11207-026-02707-0

Image Credits: AI Generated

DOI: 10.1007/s11207-026-02707-0

Keywords: sunspots, solar oscillations, infrared observations, wavelet analysis, AIMS telescope, magnetic fields, solar physics, umbra, penumbra, magneto-convection, space weather, Lenghu Observatory

The stakes of this archival detective work are higher than they might appear. French solar observations form the primary data source covering the Maunder Minimum, the period from roughly 1645 to 1715 when sunspots became vanishingly rare and Europe shivered through what climatologists call the Little Ice Age. In the 1990s, the astronomer Elisabeth Nesme-Ribes extensively analyzed the Parisian Observatory archives and published a series of influential reconstructions. Tragically, the solar data she compiled have since been lost; only a single figure of average sunspot latitudes survives. That loss made a fresh, independent reduction of the original documents not merely desirable but essential, and the new study delivers exactly that, digitizing measurements that had previously existed only in ink on paper.

The technical challenge of converting seventeenth- and eighteenth-century observations into modern solar coordinates is formidable. La Hire did not simply note that a spot existed; he measured the times at which spots crossed the solar meridian, recorded angular distances from the disk’s limbs, and drew the spots in engravings that captured their shapes and relative positions. To transform these numbers into latitudes and longitudes, the researchers needed the angular size of the solar disk on every observing day, which changes through the year as Earth moves along its elliptical orbit. They interpolated routine meridian measurements published posthumously by Le Monnier in 1741, recovering disk diameters to within a few arcseconds for dates spanning the entire eight-year window. Combining transit timings with these disk sizes, they traced each sunspot’s path across the visible hemisphere and computed daily heliographic coordinates for every individual spot and group.

The reconstruction demanded careful correction of errors scattered through the historical record. The researchers found typos in dates, mislabeled authorship, and arithmetic slips in both the journals and the printed Mémoires. On 31 May 1703, for example, La Hire made an error in a sunspot transit measurement that could only be resolved by consulting his own journal. On 26 June of that year, an engraving appears to have been accidentally reversed and flipped compared with the other drawings, a conclusion supported by the relative positions of the umbrae and by agreement with a drawing by Giovanni Domenico Cassini. On 2 January 1707, a measurement taken seven minutes after noon required a positional correction of about 3.6 degrees toward the solar Equator. Each such fix, the authors note, matters when the goal is a machine-readable catalogue that modern solar physicists can trust.

The Parisian records also proved decisive in resolving puzzles among contemporary observers across Europe. The reconstructed positions resolved an inconsistency in the observations of Johannes Hoffmann and showed that the observer Müller was using a different type of telescope, a finding that changes how his measurements should be interpreted. The team cross-checked La Hire’s data against records from the Kirch family, Hoffmann, Eimmart, Müller, Becker, Hertel, Sturm, Wideburg, Manfredi, and Derham, weaving a continental network of observations into a coherent whole. In one striking episode from January 1704, Giacomo Filippo Maraldi reported two widely separated sunspot groups on the same day, remarking that it had been a long time since such widely separated spots had been seen together, a vivid reminder of how unusual even modest solar activity had become during those years.

Among the technical fruits of the study is a new estimate of the Sun’s sidereal differential rotation during this quiet epoch. For a synodic rotation period of 27.5 days, the sidereal rotation rate works out to 14.08 degrees per day, slightly slower than the 14.18 degrees per day of the modern Carrington frame that serves as the standard reference for solar rotation today. The researchers derived rotation rates from pairs of measurements separated by hours, days, and full disk passages, tabulating them for individual spots and groups. The persistence of Joy’s law, the well-known tendency of sunspot groups to tilt with their leading spots closer to the Equator than their trailing spots, was also verified in these ancient data, suggesting that the underlying dynamics of magnetic flux emergence were operating much as they do now, even at the tail end of a grand minimum.

The time-latitude diagram constructed from the new catalogue, a butterfly-like plot showing where spots appear as the solar cycle progresses, is consistent with the previously available results from the analyses of the Parisian observations, including Nesme-Ribes’s surviving figure of average latitudes. This agreement is reassuring on two fronts: it validates the lost reconstructions of the 1990s and confirms that the new, independently derived dataset can safely replace them. The researchers also documented the Wilson effect in an unexpected place, noting that on 3 June 1703 La Hire observed a sunspot at the very edge of the disk appearing as a small depression in the limb, a phenomenon now understood to arise because spots are shallow structures rather than flat markings on a perfect sphere.

The day-to-day texture of the observations brings the era to life. La Hire frequently worked with telescopes of 16 feet and longer, switching instruments depending on conditions; on 18 January 1704 he could not discern a spot with a 3-foot tube but saw it clearly with a 16-foot one, likely because of poor contrast near the limb. Clouds, fog, and haze repeatedly interrupted the observing campaigns, and the journals candidly record blank Suns, vanished spots, and rare double appearances. In October 1705, two sunspot groups were seen simultaneously, an event the observers flagged as a rarity, and in November 1707 Cassini marveled that a spot had appeared in the northern hemisphere at a latitude of about 13 degrees, an occurrence he called extraordinary. Such details, once mere color, now feed quantitative reconstructions of the solar cycle’s recovery from its deepest recorded lull.

All of the reconstructed sunspot parameters, including daily latitudes, longitudes, areas, and counts, are provided in electronic supplementary materials accompanying the paper, giving modelers of the solar dynamo a fresh, high-resolution window onto the Sun’s behavior as it emerged from the Maunder Minimum. Understanding how the cycle recovered from that grand minimum is not just an exercise in historical astronomy; it informs how scientists assess the Sun’s capacity for prolonged lulls in activity and what such lulls might mean for climate and space weather on timescales of centuries. La Hire, sketching spots with quill and micrometer in the fog above Paris, could not have imagined that his notebooks would one day anchor twenty-first-century dynamo simulations. Three hundred years on, his patience is paying scientific dividends once again.

Subject of Research: Reconstruction of sunspot positions, areas, and counts from Philippe de La Hire's observations at the Paris Observatory during 1703 to 1710, in the late Maunder Minimum.

Article Title: Sunspot Observations by Philippe de La Hire from 1703 to 1710

Article References: Zolotova, N., & Vokhmyanin, M. (2026). Sunspot Observations by Philippe de La Hire from 1703 to 1710. Solar Physics, 301(9), Article 133. https://doi.org/10.1007/s11207-026-02719-w

Image Credits: AI Generated

DOI: 10.1007/s11207-026-02719-w

Keywords: sunspots, Maunder Minimum, solar cycle, solar physics, Philippe de La Hire, Paris Observatory, solar rotation, Joy's law, historical astronomy, sunspot records, solar dynamo, space climate

The study, conducted by Owen Giersch, analyzed X-ray flares of M class and higher—the moderate to extreme events that matter most for space weather operations. The research took two complementary approaches. First, flares were sorted into logarithmically spaced intensity categories and compared across sunspot cycles. Second, flare rates were tabulated according to the McIntosh classification of the sunspot group that produced each event, allowing a direct test of whether a given type of sunspot region flares at the same rate regardless of which cycle it belongs to. Both tests delivered results that depart from the comforting assumption of cycle-to-cycle consistency.

The McIntosh classification scheme, which underpins the second part of the analysis, has a long pedigree. Sunspot classification began with Alfred Cortie’s scheme of 1901, which is no longer used. Observers in Zurich developed an alternative system in the 1930s, using nine categories to describe the evolution of sunspot groups. In the 1960s, Patrick McIntosh modified this Zurich system, removing two classes and adding parameters describing the penumbra of the largest sunspot in a region and the compactness of spots within the region. The resulting Modified Zurich Classification—now universally known as the McIntosh system—combines the Zurich class, the penumbral character, and the compactness into 60 permitted classes. Because sunspot classification serves as a proxy for the magnetic complexity of an active region, it remains the backbone of most flare forecasting practice.

The data underpinning the analysis came from two archival sources. For flares prior to 1996, records were obtained from the National Centers for Environmental Information, and from 1996 onwards from the Space Weather Prediction Center, both drawing ultimately on the GOES satellite series that has monitored solar X-ray output continuously since cycle 21. Sunspot region reports came from United States Air Force Solar Observing Optical Network sites, whose daily observations include quality flags ranging from 1, indicating very poor seeing conditions, to 5, indicating excellent conditions. Because pre-1996 reports were listed from up to five individual sites without being reduced to a single classification, the author developed a method to consolidate multiple daily reports: retaining the highest-quality report, then adopting the most frequently occurring class, with random selection only in the rare case of irreconcilable ties.

The data cleaning itself illustrates the messy reality of half a century of observational records. Numerous invalid classifications appeared in the archive—classes with missing or implausible parameters—and a set of explicit rules was applied to correct them, drawing on the physical logic of the McIntosh scheme. After all corrections, only 193 regions could not be assigned a valid class, and these were omitted from the analysis. For the flare-rate comparison by sunspot class, only flares with an assigned region were included, while the raw cycle-to-cycle flare counts used all reported events. This careful curation matters, because the study’s conclusions hinge on comparisons between data streams that were assembled by different teams, with different instruments and practices, across 50 years.

The statistical machinery was deliberately conventional, designed to be transparent rather than exotic. To compare flare intensity distributions between two cycles, a chi-squared test was employed, with categories combined wherever either distribution contained fewer than five flares, and p-values computed so that distributions could be deemed similar at the 95 percent confidence level. To compare flare rates by McIntosh class, both chi-squared tests and linear regression were used. Under the regression approach, if two cycles behaved identically, plotting one cycle’s flare rates against the other’s should yield a line with a gradient of one, an intercept of zero, and a correlation coefficient close to one. Departures from that ideal indicate genuine differences in how sunspot classes translate into flares.

The results on intensity are nuanced but troubling. At the 95 percent confidence level, the flare intensity distribution of cycle 21 cannot be considered similar to those of cycles 22 through 25—a discrepancy the author attributes in part to the fact that cycle 21 was the first cycle during which the GOES satellites operated, raising the possibility of calibration or measurement issues. The comparisons between cycles 22 and 25 and between cycles 23 and 25 also failed the similarity test. A broad pattern emerged: the greater the separation between two cycles in time, the more dissimilar their flare intensity distributions tend to be. The striking exception is the pairing of cycles 22 and 24, which produced the highest p-value of any comparison, suggesting those two cycles flared in remarkably similar proportions despite differing in overall amplitude.

The second finding is more fundamental. When flare rates were compared by McIntosh class across cycles, chi-squared tests found essentially no pairs of cycles that could be considered similar. The sole nominal exception—a comparison of cycle 21 as the observed distribution against cycle 22 as the expected distribution—flipped to dissimilar when the roles were reversed, a signature of a statistical false positive. The regression analysis reinforced the picture: while the intercepts of seven out of ten cycle comparisons were close to zero, as expected for the least active sunspot classes, only the comparisons involving cycles 25 and 22 produced gradients close to one. In plain terms, the rate at which a given kind of sunspot group produces M-class or larger flares varies significantly from one solar cycle to another.

What explains this variability? The study is candid that the answer remains unclear. One possibility is observer bias: sunspot classification is a human judgment, and many researchers have documented problems with sunspot group analysis, particularly with sunspot areas, which form one input to the McIntosh parameters. If area measurement techniques—and therefore the resulting values—have drifted over decades, other derived parameters such as extent and compactness may have drifted too, contaminating any cycle-to-cycle comparison. The alternative is more provocative: that the difference reflects a genuine physical change in how the Sun organizes magnetic energy from cycle to cycle. Intriguingly, recent work by other researchers found that as the McIntosh Zurich class increases from A to F, the total magnetic energy of active regions rises, but the free energy—the portion available to power eruptions—does not change significantly, hinting that classification alone may not capture what makes a region flare-ready.

Despite the ambiguities, the analysis closes with something immediately useful for forecasters. Assuming flares follow a Poisson process, the probability of at least one M-class or larger flare occurring in a given region over a specified interval can be computed from its flare rate, and with multiple regions on the Sun—common near solar maximum—the combined probability follows from multiplying the individual exponential terms. The full dataset generated for the study has been released in a public GitHub repository, and the author emphasizes that further analysis of the USAF sunspot classifications is needed to determine whether the cycle-to-cycle variation is intrinsic to the Sun or an artifact of evolving observational practice. Either answer carries weight: one rewrites the physics of flare statistics, the other a cautionary tale about the archives on which space weather science is built.

Subject of Research: Statistical analysis of X-ray solar flare intensity distributions and flare rates by McIntosh sunspot class across solar cycles 21 to 25

Article Title: Analysis of X-ray Solar Flare Rates from 1976 to 2025

Article References: Analysis of X-ray Solar Flare Rates from 1976 to 2025. (n.d.). https://doi.org/10.1007/s11207-026-02743-w

Image Credits: AI Generated

DOI: 10.1007/s11207-026-02743-w

Keywords: solar flares, X-ray flares, sunspots, McIntosh classification, solar cycle, space weather, GOES satellites, flare forecasting, solar physics, statistical analysis, sunspot classification, active regions

The study, published in the journal Solar Physics, was carried out by V. N. Obridko of the Pushkov Institute of Terrestrial Magnetism, Ionosphere and Radio Wave Propagation (IZMIRAN), M. M. Katsova of the Sternberg Astronomical Institute at Lomonosov Moscow State University, and D. D. Sokoloff of the Faculty of Physics at Lomonosov Moscow State University. Their work draws on the full record of soft X-ray flare monitoring by the Geostationary Operational Environmental Satellites, or GOES, which began in 1975 and has provided the standard classification of solar flares ever since. That continuous, homogeneous dataset is what makes a statistically meaningful look at flare behavior across multiple cycles possible.

Solar flares are classified by their peak soft X-ray brightness as measured by the GOES instruments, with X-class flares representing the most powerful events, each releasing energy equivalent to billions of megatons of TNT. The researchers focused on the great flares, from the relatively moderate X4 class up to the extreme X10 class and beyond, and asked a deceptively simple question: where on the solar disk do these events occur, and how does their location and frequency change as the solar cycle progresses? To answer it, they traced the latitudinal distribution of X-class flares throughout four cycles and compared the flare positions directly with the structure of the Sun’s large-scale magnetic field.

The picture that emerges is one of overlapping magnetic waves. Over the course of a solar cycle, the zones where sunspots and active regions appear migrate steadily from mid-latitudes toward the equator, a pattern known since the nineteenth century as Spörer’s law. At the same time, a second wave of activity belonging to the next cycle begins at higher latitudes and propagates poleward. The new analysis shows that the relatively weak members of the great-flare family, those in the X4 to X7 range, tend to occur at relatively high latitudes of roughly 15 to 20 degrees, precisely where these two waves of activity converge: one moving equatorward as the current cycle matures, and the other, the wave of the following cycle, directed poleward. These events are observed almost continuously during the one to two years before the cycle maximum.

The most powerful flares, however, tell a different story. The total number of powerful X-ray flares increases sharply during the maximum phase of the cycle, as expected from the sheer abundance of magnetically complex active regions. But the greatest events, those of X10 class and stronger, are largely absent during the growth phase of the cycle. Instead, they begin to appear one to two years before the maximum number of sunspots is reached, during the overlapping phase when different kinds of activity waves coexist on the Sun at relatively high latitudes. They then continue to appear throughout the declining phase, at the boundary that separates the wave of local fields from the poleward wave of the following cycle.

This timing is significant because it challenges the simplest expectation that flare intensity should peak exactly when sunspot numbers do. The researchers’ conclusion is that the greatest X-ray flares are not merely a byproduct of having many sunspots, but are tied to a specific magnetic configuration that arises when the outgoing and incoming activity waves overlap. In dynamo theory, the solar cycle is understood as a propagating wave of magnetic field generated by the interplay of turbulent plasma motions and the Sun’s rotation, and the interaction zones between successive waves provide conditions in which magnetic fields of opposite polarity and different origins can be forced together, building up the enormous stresses that power the largest eruptions.

The technical foundation of the analysis rests on comparing flare positions with synoptic maps of the photospheric magnetic field, which chart the distribution of magnetic flux across the solar surface over each solar rotation. The magnetic field data were drawn from the synoptic program at Stanford University’s Wilcox Solar Observatory, while sunspot numbers came from the World Data Center SILSO at the Royal Observatory of Belgium. By overlaying the latitudes of great flares on these magnetic structures, the team could show that flare sites are not randomly distributed within the activity belts but are preferentially located at the interfaces between magnetic regimes, where the wave of local active-region fields meets the large-scale poleward-migrating field of the next cycle.

The practical implications of this finding reach well beyond solar physics. Great X-class flares, particularly when accompanied by coronal mass ejections, are the primary drivers of space weather, capable of disrupting satellite operations, radio communications, GPS navigation, and power grids on Earth. The May 2024 G5-level geomagnetic storm, triggered by a barrage of eruptions from a single enormous active region, offered a vivid recent reminder of how much is at stake. If the largest flares preferentially occur in the years around and after sunspot maximum, and especially at the magnetic boundaries identified in this study, then space-weather forecasting could gain a valuable statistical tool: the periods of greatest extreme-flare risk may extend well past the sunspot peak, rather than ending with it.

The results also connect to a broader body of research on the extended solar cycle and the large-scale magnetic field. Earlier work by members of the same team has traced cyclic variations in the main components of the Sun’s large-scale magnetic field and examined the asymmetry introduced by the extended cycle, in which traces of the next cycle appear years before the current one fades. The new flare analysis adds an independent observational thread to this picture, suggesting that the overlap of activity waves is not a subtle theoretical curiosity but a physically consequential configuration that leaves a measurable imprint on the most energetic events in the solar system.

For now, the study’s conclusions rest on four cycles of GOES data, a sample that is large enough to reveal the pattern but still limited in the sense that each solar cycle has its own character. Some cycles are strong and some are weak, and the recalibration of the greatest GOES soft X-ray flare measurements across two Hale cycles remains an active area of research. Nevertheless, the message of the new work is clear and testable: to understand when the Sun will unleash its very worst, astronomers need to look not only at how many sunspots dot the surface, but at where two great waves of solar magnetism meet and mingle. As the current cycle progresses toward and past its maximum, the boundaries identified in this study will be among the most closely watched regions on the Sun.

Subject of Research: Cycle-dependent latitudinal occurrence of great soft X-ray solar flares in relation to overlapping solar magnetic activity waves

Article Title: Cycle Variation in the Occurrence of Great Soft X-ray Solar Flares

Article References: Obridko, V. N., Katsova, M. M., & Sokoloff, D. D. (2026). Cycle Variation in the Occurrence of Great Soft X-ray Solar Flares. Solar Physics, 301(9), Article 140. https://doi.org/10.1007/s11207-026-02732-z

Image Credits: AI Generated

DOI: 10.1007/s11207-026-02732-z

Keywords: solar flares, X-class flares, solar cycle, space weather, solar magnetic field, GOES, solar dynamo, sunspots, Solar Physics, coronal mass ejections, activity waves, solar maximum

The green line at 530.3 nanometers is the brightest emission line in the solar corona, produced by highly ionized iron atoms, Fe XIV, stripped of thirteen of their electrons by the extreme coronal temperatures of roughly two million kelvin. Unlike the photospheric surface we see with the naked eye, the corona traces magnetic structures that arch high above active regions, and its emission intensity varies with the strength and distribution of the underlying magnetic field. Because ground-based observatories, coordinated through networks that produced the green corona database and the coronal index of solar activity, have monitored this emission consistently since the mid-twentieth century, the green line provides an exceptionally long and homogeneous record of large-scale coronal behavior that modern space-based instruments simply cannot match in duration.

On the sunspot side, the study departs from tradition in a crucial way. Conventional analyses of the solar cycle often rely on the sunspot number or the total sunspot area, both of which collapse the entire two-dimensional distribution of spottedness into a single scalar per day. Takalo instead constructed a Gaussian representation of the sunspot activity field, built from the individual areas and latitudes of every recorded sunspot group. This activity-field model preserves where on the solar disk the magnetic flux emerges, capturing the characteristic equatorward migration of sunspot belts as each cycle progresses and the poleward drift of its remnants. The result is a mathematical description of the large-scale spatial organization of solar magnetic activity that is far more realistic than any single-number index.

The central discovery of the study is a remarkably stable, double-peaked correlation structure in latitude. When coronal green-line emission at each latitude band is correlated against the modeled sunspot activity field at the same latitude, the correlation profile shows two strong maxima that track the well-known active-region belts on either side of the solar equator. These peaks, typically centered in the low and mid-latitudes where sunspot groups preferentially emerge, remain strikingly similar in shape and position from one cycle to the next. Even between weak cycles and strong cycles, and between even-numbered and odd-numbered cycles with their differing amplitudes and parity, the latitude profiles of the corona–sunspot relationship barely change, indicating that the large-scale coupling between photospheric activity and coronal emission is largely independent of how vigorous any particular cycle happens to be.

This finding carries weight because solar cycles are far from identical twins. Cycle 19, which peaked in the late 1950s, was the most active in the observational record, while Cycle 24 was notably feeble, and the even–odd alternation in cycle strength, sometimes called the Gnevyshev–Ohl rule, hints at deep-seated differences in the solar dynamo from one cycle to the next. Yet the corona appears to respond to the sunspot engine in a nearly invariant geometric pattern. The double-peaked structure is a direct signature of the fact that green coronal emission is strongest not randomly across the disk but precisely where active-region magnetic fields cluster, confirming quantitatively what decades of qualitative observation have suggested: the corona is, in a very real sense, a magnetic portrait of the activity belts painted in glowing iron light.

Perhaps the most subtle part of the analysis concerns timing. Using lag-correlation techniques, the study finds that the strongest correlations between the coronal emission and the sunspot activity field generally occur at positive lags, which would naively suggest that the corona follows the sunspots with a specific, measurable delay. But here the author applied a rigorous statistical safeguard. Surrogate-data tests, in which the temporal ordering of one record is scrambled while its statistical properties are preserved, show that these formal lag maxima are usually not statistically distinguishable from the correlations at neighboring lag values. The lag-correlation profiles instead display broad, flat positive-lag plateaus, meaning the apparent delay is not a sharply defined physical delay at all.

What the plateaus do reveal is something arguably more interesting: temporal persistence and memory in the large-scale coronal magnetic structures. Rather than the corona slavishly tracking each new burst of sunspot emergence after a fixed interval, the green-line emission behaves like a slowly evolving reservoir that integrates and smooths the photospheric activity underneath it. Magnetic fields introduced into the corona by emerging active regions persist, relax, and redistribute over extended timescales, so the coronal response is broad and smeared rather than impulsive. This interpretation aligns with a growing body of work emphasizing that the large-scale distribution of magnetic flux, spanning scales far beyond individual sunspots, governs the evolution of the corona as a global system.

The comparison between modeling approaches proved decisive in this regard. When the Gaussian activity-field representation was used as the predictor of coronal emission, it produced substantially stronger and more coherent correlations than conventional sunspot number or sunspot area measures ever achieved. In other words, knowing not just how many sunspots exist but where they sit on the disk at any moment allows a far better reconstruction of the green-line corona’s behavior. This supports the central physical conclusion of the paper: that it is the large-scale spatial distribution of magnetic activity, rather than the presence of individual sunspots alone, that controls the evolution of the large-scale corona. For modelers of the solar atmosphere, this is an invitation to move beyond scalar activity indices toward genuinely two-dimensional descriptions of the emerging flux.

The practical implications extend beyond pure solar physics. The green corona has long served as a proxy for solar activity in space-weather and solar-terrestrial research, and the coronal index built from it has been used to study everything from geomagnetic disturbance to long-term solar variability. Establishing that the corona’s response to sunspot activity is stable in latitude, amplitude-independent, and temporally diffuse strengthens confidence in using coronal records to extend our knowledge of solar behavior backward in time and, potentially, to refine reconstructions of past solar cycles. It also cautions against overinterpreting any single lag measurement as a physical delay mechanism, a lesson in statistical humility that applies across solar-terrestrial science.

Spanning seven decades and seven solar cycles, this analysis demonstrates that beneath the Sun’s famously variable surface behavior lies an unexpectedly disciplined architecture. The green-line corona and the sunspot belts are locked together in a latitude-dependent partnership whose geometry survives even the wildest swings in cycle strength, while their timing relationship reflects the lingering memory of magnetic structures rather than any simple cause-and-effect delay. As the Sun progresses through Cycle 25 and observers accumulate fresh coronal data, the stable patterns documented here provide a robust baseline against which any genuine, long-term change in solar behavior can be recognized. In the quiet green glow of iron atoms two million degrees hot, the Sun has written down, cycle after cycle, a remarkably consistent record of its own magnetic heartbeat.

Subject of Research: Latitude-dependent relationships between green-line coronal emission and sunspot activity across Solar Cycles 18–24

Article Title: Large-Scale Latitude-Time Relationships Between the Green-Line Corona and Sunspot Activity During Solar Cycles 18 – 24

Article References: Large-Scale Latitude-Time Relationships Between the Green-Line Corona and Sunspot Activity During Solar Cycles 18 – 24. (n.d.). https://doi.org/10.1007/s11207-026-02729-8

Image Credits: AI Generated

DOI: 10.1007/s11207-026-02729-8

Keywords: solar corona, green coronal line, sunspots, solar cycle, solar magnetic fields, activity belts, lag correlation, surrogate data, solar physics, coronal index, solar dynamo, space weather