Tree Rings and Cosmic Rays Reveal a Thousand Years of Sunspot Cycles Without the Negative-Number Problem

For four centuries, astronomers have counted the dark blemishes that drift across the face of the Sun, and from those counts they have built one of the longest quantitative records in all of science: the sunspot number. But the telescopic era is a brief snapshot against the Sun’s full history. To understand how our star behaved before Galileo first pointed his spyglass skyward, researchers must turn to indirect witnesses, and none are stranger or more valuable than the radioactive fingerprints locked inside tree rings and polar ice. A new study published in the journal Solar Physics now presents a fundamentally rebuilt method for converting those fingerprints into a thousand-year, year-by-year reconstruction of sunspot activity, one that finally solves a stubborn problem that has plagued the field for years: reconstructions that occasionally produced negative sunspot numbers, a result that is statistically possible but physically absurd.

The chain of causality that makes such reconstructions possible begins far beyond Earth. The Sun’s magnetic field, dragged outward by the solar wind, fills the heliosphere, the vast protective bubble surrounding the solar system. Galactic cosmic rays, high-energy particles arriving from outside, must fight their way through this magnetic shielding to reach Earth. When the Sun is magnetically active, the shielding strengthens and fewer cosmic rays penetrate; when the Sun quiets, the floodgates loosen. Upon entering the atmosphere, cosmic rays collide with nitrogen, oxygen and argon, spawning showers of secondary particles that forge rare radionuclides such as carbon-14 and beryllium-10. Carbon-14, once formed, is incorporated into carbon dioxide, absorbed by trees during photosynthesis and permanently archived in annual growth rings. Because a magnetically active Sun suppresses cosmic ray influx, the abundance of these isotopes in wood and ice is inversely correlated with solar activity, giving scientists a decipherable record stretching back thousands of years.

Deciphering it, however, is harder than it sounds. Previous reconstruction efforts relied on statistical regressions that mapped isotope-derived quantities onto sunspot numbers, and those regressions carried hidden dangers. As the new study’s authors, led by Chitradeep Saha of the University of Reading, point out, even a regression with an impressively high correlation coefficient can misfire if the data contain non-linearities, zero-level offsets, or uneven variance across amplitudes. The most notorious failure mode appears during grand minima, the extended intervals when solar activity collapses, such as the Maunder minimum of the seventeenth century. When regression equations calibrated on modern data are extrapolated to these unusually quiet conditions, they can yield sunspot numbers below zero. Values are often simply clipped to zero, but that crude fix distorts cycle averages and inflates estimates of the Sun’s total irradiance, which in turn muddies attempts to understand the Sun’s influence on past climate.

The Reading-led team, which also includes Mathew Owens, Mike Lockwood and Luke Barnard, together with colleagues at ETH Zurich, the University of Lancashire, the University of Oslo, Lund University and the University of Groningen, took a different path. Rather than inverting the physics with a regression, they ran it forward, over and over, in a Monte Carlo framework. The method, implemented in publicly released code under the name PRISM, begins by generating an ensemble of thousands of hypothetical sunspot cycles drawn from statistical priors: cycle amplitudes sampled from a log-normal distribution, cycle lengths from a Gaussian distribution centred on 10.5 years, and a random start offset for each window of time. Each trial cycle is then passed through a sequence of two semi-empirical forward models that translate sunspot number into open solar flux, the total magnetic flux threading the outer boundary of the corona, and then into the heliospheric modulation potential, a quantity describing how much energy cosmic rays lose as they traverse the heliosphere.

The forward models rest on decades of established solar physics. The first couples sunspot number to the emergence of new magnetic flux through a empirically optimised source function, balanced against a phase-dependent loss rate derived from solar cycles 13 through 24. The second model computes the modulation potential from the open flux together with the tilt and polarity of the heliospheric current sheet, following a formulation calibrated by Owens and colleagues in 2024. Crucially, the open solar flux evolves with memory: it accumulates from past sunspot activity and decays through magnetic reconnection, introducing a hysteresis that makes the inverse problem fundamentally non-unique. Multiple distinct sunspot histories can produce statistically indistinguishable modulation records, which is precisely why simple deterministic inversions break down.

To handle that non-uniqueness, the team employed Approximate Bayesian Computation, a statistical technique that sidesteps the need for an explicit likelihood function. In each sliding ten-to-fifteen-year window, ten thousand Monte Carlo realisations of sunspot cycles are propagated through the forward models and compared directly against the observed modulation potential using a weighted Euclidean distance. The best two percent of candidates, some two hundred realisations, are retained as samples from the approximate posterior distribution, and their spread provides rigorous, quantified uncertainty bounds reported as 68 percent highest-density intervals. Because the sunspot cycle amplitudes are constrained to be non-negative by construction, the resulting reconstruction can never produce the negative values that haunted earlier regression-based approaches, and it requires no post-hoc correction.

To test the method, the researchers applied it to two annual-resolution records of the modulation potential. The first, spanning 1845 to 2020, was derived from geomagnetic observations of open solar flux by Owens and colleagues. When used as the inversion target, the method recovered sunspot numbers and open flux in close agreement with the direct instrumental record maintained by SILSO, with a mean absolute error of just 19.25 megavolts, about three percent of the mean modulation potential. That success validated the technique and justified applying it to the second, far longer dataset: a radiocarbon-based modulation potential record covering 971 to 1932, reconstructed by Nicolas Brehm of ETH Zurich and colleagues from tree-ring carbon-14 measurements. Before feeding the tree-ring record into the inversion, the team cross-calibrated it against the geomagnetic record over their overlapping decades, applying an additive correction of 65.76 megavolts that statistical tests showed produced a near-perfectly symmetric, homoskedastic residual distribution.

The millennial-scale reconstruction that emerged is rich with detail. It captures the familiar grand minima and maxima of the past thousand years, including the Maunder minimum, the Spörer minimum, the Dalton minimum, and the double-peaked grand maximum the Sun passed through between 1900 and 2020. Crucially, the reconstructed open solar flux never falls to zero. Even during the deepest quiet of the Spörer minimum, the unsigned open flux dropped only to about 1.21 times ten to the fourteen webers in 1443, the lowest value in the entire record and well below anything observed in the telescopic era, yet still decisively nonzero. During the Maunder minimum the flux averaged around 2.63 times ten to the fourteen webers. This confirms that the solar dynamo never fully shuts down during grand minima but instead idles in a reduced, finite activity state, a conclusion consistent with flux transport dynamo models in which meridional plasma circulation sustains weak cycles and eventually drives recovery.

The new record also documents some striking extremes at the other end of the scale. The peak annual open solar flux of the twentieth century, reached in 1958, was about 10.96 times ten to the fourteen webers, the highest since the year 1200. Only three years in the entire millennium exceeded it, the largest peaking at roughly 14.21 times ten to the fourteen webers in 981 CE, shortly after the record begins. In other words, the era of telescopic observation has sampled a large fraction, but not all, of the Sun’s true dynamic range; deeper minima and higher maxima both occurred before instruments existed to see them. The reconstruction also flags three intervals around 993, 1052 and 1279 CE where proposed Miyake events, extreme solar particle storms recorded as abrupt radiocarbon spikes, contaminate the cosmic-ray-based record, and the authors conservatively mask these windows from their results.

Beyond its intrinsic appeal as a thousand-year diary of solar magnetism, the work has immediate practical value. Annually resolved, physically consistent sunspot numbers feed directly into reconstructions of total and spectral solar irradiance, which in turn constrain climate models exploring the Sun’s role in terrestrial temperature variability over past centuries. The uncertainty-quantified cycle amplitudes during grand minima provide empirical targets for solar dynamo theorists probing the minimum operating point of the solar cycle engine. The authors note that their forward model templates were built from modern, regular solar cycles, so reconstructions of grand minimum cycles should be treated as indicative rather than definitive, and that the additive cross-calibration between the two modulation potential datasets is itself a simplification. Even so, the framework offers what the team describes as a probabilistic ensemble of physically admissible solar histories rather than a single deterministic answer, and it opens the door to pushing the same technique further back in time as longer and older cosmogenic isotope records become available. The Sun, it turns out, kept meticulous records all along; the trick was learning to read them without breaking the laws of physics.

Subject of Research: Physics-constrained reconstruction of annually resolved sunspot numbers from millennial-scale heliospheric modulation potential records.

Article Title: Physics-Constrained Reconstructions of Sunspot Number from Millennial-Scale Annual Heliospheric Modulation Potential

Article References: Saha, C., Owens, M., Lockwood, M., Barnard, L., Brehm, N., Dalla, S., Herbst, K., Muscheler, R., & Wang, J. (2026). Physics-Constrained Reconstructions of Sunspot Number from Millennial-Scale Annual Heliospheric Modulation Potential. Solar Physics, 301(9), Article 144. https://doi.org/10.1007/s11207-026-02731-0

Image Credits: AI Generated

DOI: 10.1007/s11207-026-02731-0

Keywords: sunspot number, solar cycle, heliospheric modulation potential, cosmogenic isotopes, radiocarbon, open solar flux, Maunder minimum, Spörer minimum, approximate Bayesian computation, space climate, solar dynamo, galactic cosmic rays