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