Soft X-Ray Emission from Saturn's Magnetosheath II: Solar Wind Driving
By Dan Naylor (Lancaster University)
Saturn’s magnetosphere is dominated by Enceladus-sourced, water-group neutrals that form a torus and extend into the magnetosheath. Soft X-ray emission can be generated in the magnetosheath due to charge exchange between highly charged solar wind ions and the neutrals. Imaging of the soft X-rays is an emerging technology that aims to provide a more global and dynamic view of the magnetosheath and, for example, give insights into the driving of the magnetosphere by the solar wind. The ESA/CAS SMILE mission has now launched and aims to image the terrestrial magnetosheath. We, along with Rogan et al. (2026, https://doi.org/10.1029/2025JA034462), explore the viability of soft X-ray imaging at Saturn. We consider charge exchange between Enceladus-sourced H, O and OH and solar wind ions O7+ and O8+ to estimate the emission rates from the system and the flux detected by a soft X-ray imager (SXI) at the system. We also vary solar wind dynamic pressure to test the effect of changing solar wind conditions on X-ray production. X-ray volumetric emission rate is on the order of 10-11 to 10-10 photon cm-3 s-1 for slow and fast solar winds. For a SMILE-like SXI imaging the system from around 50 RS, >100 photons could be detected within a quarter of a planetary rotation. A hypothetical future instrument with increased FOV and effective area significantly increases photon count rate, highlighting that X-ray imaging may be a useful technique to better understand Saturn’s magnetosphere and neutral environment on a potential future mission.
See publication for more details:
Naylor, D., Ray, L. C., Rogan, P. C., Dunn, W. R., & Smith, H. T. (2026). Soft X-ray emission from Saturn's magnetosheath II: Solar wind driving. Journal of Geophysical Research: Space Physics, 131, e2025JA034461. https://doi.org/10.1029/2025JA034461

Emission rate slices (a, b, c) in the y-z, x-y and x-z planes and modelled intensity maps (d, e, f) for a nose-on, top-down and side-on view of the system, for a SMILE-like soft X-ray imager at ~50 RS from Saturn.
Which Kelvin-Helmholtz waves grow along the spatially-varying magnetopause flanks and why?
By Harley Kelly (Imperial College London)
The Kelvin-Helmholtz instability mediates the viscous-like solar-terrestrial interaction, allowing solar wind plasma and energy to penetrate our magnetic shield through generating magnetopause surface waves that quickly become non-linear. Determining when and where this should occur and which wave modes grow has remained challenging. This is because the underlying theory has concentrated on local wave growth, where the locally most-unstable linear wave dominates. However, these waves travel along the boundary into new regions where the instability is still able to amplify these perturbations despite the different background properties. Two possible paradigms exist, waves are either:
(a) locally generated, being those predicted by the simple theory
(b) originate further upstream, having travelled and grown along the way
We address this conundrum by applying a machine learning technique, Dynamic Mode Decomposition, that efficiently extracts distinct wave modes from a simulation of the entire magnetosphere. This shows Kelvin-Helmholtz waves do grow quickly out of some points on the boundary, signaling local generation. However, their energy persists as they travel down the tail, slowly growing in both amplitude and spatial extent in the process due to the accelerating flow around the magnetosphere and its effect on the instability. Therefore, both effects play a role in which waves are dominant at any point.
These results may explain why longer wavelengths are observed in the tail than local theory predicts and motivates further exploration of tangential inhomogeneities in basic Kelvin-Helmholtz theory. We also highlight that Dynamic Mode Decomposition may prove a powerful technique for studying other forms of waves, instabilities and turbulence across the heliosphere.
See publication for more details:
Kelly, H. M., Archer, M. O., Eastwood, J. P., Heyns, M., Eggington, J. W. B. and Chittenden, J. P (2026). Superposition of Doppler-Shifting Magnetopause Kelvin-Helmholtz Modes Through Dynamic Mode Decomposition of a Global MHD Simulation. Geophysical Research Letters, 53, e2025GL120284, https://doi.org/10.1029/2025GL120284

Comparison of dynamic mode decomposition modes along equatorial magnetopause tangent showing (a) integrated energy densities and (b) polynomial-fit wavelengths. (c) Cartoon depicting key results.
A new declining phase precursor and an early prediction of cycle 26 maximum
By Sandra Chapman (CFSA, Physics, University of Warwick)
The solar polar magnetic fields during the declining phase of each Schwabe solar cycle 'seed' the toroidal fields that drive sunspot activity of the next cycle. This paper identifies the specific phase of the cycle, and hence the timing, where this relationship should unambiguously be seen, both in models and in high resolution observations. This is central to comparing observations with solar dynamo models as well as providing a precursor method to forecast the upcoming cycle maximum.
The Hilbert transform of 13 month smoothed sunspot number (SSN) since 1749 is used to construct a uniform clock for the Schwabe solar cycle which establishes a clear switch-on and off of geomagnetic activity seen at earth [1] and which correlates with solar morphology on solar cycle scales [2]. By mapping the irregular solar cycle onto a regular clock, the timings of a clear switch-off of activity in the cycle declining phase have been found. The switch-off is when solar eruptions change in character from coronal mass ejections to high speed streams, correlating both with the sunspot active regions moving to lower solar latitudes with reduced differential rotation, and the switch-off of extreme space weather at earth. The SSN at the switch-off is found to correlate well with the following SSN maximum, providing a method for predicting the upcoming cycle maximum on a ~7 year time horizon [3].
[1] S. C. Chapman, S. W. McIntosh, R. J. Leamon, N. W. Watkins, Quantifying the solar cycle modulation of extreme space weather, Geophysical Research Letters, (2020) doi:10.1029/2020GL087795
[2] S. C. Chapman, T. Dudok de Wit, A solar cycle clock for extreme space weather. Sci Rep 14, 8249 (2024). doi:10.1038/s41598-024-58960-5
[3] S. C. Chapman, A new declining phase precursor and an early prediction of cycle 26 maximum, Ap. J. in press (2026) doi:10.3847/1538-4357/ae6859
See publication for more details:
S. C. Chapman, A new declining phase precursor and an early prediction of cycle 26 maximum, Ap. J. in press (2026) doi:10.3847/1538-4357/ae6859

Correlation of the solar maximum sunspot number (SSN) with preceding solar cycle declining phase. Linear regression (black lines) with 68% and 95% confidence bounds (dark and light green shading) of each SSN solar maximum from SILSO plotted versus preceding cycle SSN at switch-off. Black circles indicate each cycle.