MIST

By Mike Lockwood (University of Reading)

We have studied the evolution of the debris cloud generated by the high-altitude Anti-Satellite (ASAT) test on the Fengyun-1C satellite over the subsequent 18 years. More of the objects at sizes above 10cm have survived than was predicted four years after the ASAT test, despite the average space weather activity being higher than was assumed in making those predictions. We show how debris accelerated by the test into high-apogee orbits has acted as a reservoir, giving a long-lived supply of objects ready to start the reentry spiral. The average rate of descent varies with the solar cycle and with the solar rotation period because of the variation in EUV heating of the thermosphere. Geomagnetic storms
have a short-lived but significant effect on the altitude decay of the debris, the upper decile of geomagnetic activity accounting for 12% of the lost altitude at 400 km, rising to 19% at 700km. A second, more subtle, geomagnetic effect is seen to be present, identified as being driven by the Russell-McPherron effect on solar wind-magnetosphere couplingand thermospheric heating. The contribution of this mechanism to the semi-annual variation in average debris descent speed is greatest at high altitudes but other thermospheric effects, such as wave and tide dissipation and circulation changes, are more important at lower altitudes. At times of low solar activity the EUV heating is the dominant effect but the total geomagnetic contribution is more significant during disturbed times. We discuss how these results are of importance to controlled de-orbiting of space junk.

References
M. Lockwood, C. J. Scott, J. O'Donoghue, M. J. Owens, and L. A. Barnard (2026)
The contribution of the Russell-McPherron effect to the semiannual variation in thermospheric density, J. geophys. Res. Space Phys., 131, e2025JA034732, doi: 10.1029/2025JA034732
M. Lockwood (2025) The Celestial Rubbish Dump, Astronomy and Geophysics, 66 (3), 3.36–3.42, doi: 10.1093/astrogeo/ataf023

See publication for more details:
M. Lockwood, M.J. Owens, C. Saha, L.A. Barnard, C.J. Scott, and J. O’Donoghue (2026) Space Weather, Submitted

Comparison of days with predominant positive (left) and negative (right) IMF Y-component in the GSEQ frame. Parts A and D show the FY-1C debris descent speed, v, as a function of altitude, h, and fraction of a calendar year, F, where its annual variation due to Sun-Earth distance a (as a function of h) has been subtracted to reveal the semi-annual variation. Parts C and F show the height profiles of (v-a) at the dates of peak Russell-McPherron effect in March (green) and September (mauve). Parts B and E show the variation with F of the average (v-a) over the full height range. The Russell-McPherron effect enhances the March/September peak when the Y-component in GSEQ is negative/positive and so can be clearly seen to be driving a semi-annual variation in debris descent speed at higher altitudes.

By Neil Rogers (Lancaster University)

Many of us use the NASA “OMNI” database, which takes measurements from spacecraft (e.g., ACE or Wind) near the L1 Earth-Sun Lagrange point and uses them to predict solar wind conditions near the Earth’s bow shock nose. The question is: How accurate are these OMNI predictions? This is particularly topical given recent studies showing that measurement uncertainty could explain saturation in magnetospheric responses to solar wind driving (e.g., Sivadas et al. (2026), Nature, https://doi.org/10.1038/s41586-026-10757-4). We have compared 1-min resolution OMNI predictions of plasma density, velocity, and magnetic field with concurrent ‘ground truth’ measurements from two ESA Cluster spacecraft when they were located in the solar wind in years 2001 - 2023. After calibrating ‘systematic’ linear (instrumental) biases between pairs of spacecraft, we quantified and parameterised probability density functions (PDF) of the ‘stochastic’ differences between OMNI and Cluster. We found that many of these PDFs had a very narrow central peak (i.e., most differences were close to zero) but had ‘heavier tails’ in comparison with the Normal distribution (i.e., a greater likelihood of the largest differences). The Student’s-t distribution is a good fit for these cases, although we found the five-parameter Generalised Hyperbolic distribution provides the best characterisation of the rarest and largest differences (the outermost tails of the PDFs). Our paper provides a full quantification of both systematic and stochastic uncertainties, which could be used to place more realistic uncertainty bounds on analyses and forecasts that rely on OMNI data. Our database of times for which Cluster spacecraft were in the solar wind (~ 5000 hours) at various distances beyond the bow shock is also available to download: https://doi.org/10.5281/zenodo.18390327.

See publication for more details:
Rogers, N. C., Wild, J. A., & Grocott, A. (2026). Quantifying uncertainty in OMNI solar wind measurements projected from L1 to the Earth's bow shock. Journal of Geophysical Research: Space Physics, 131, e2026JA035221. https://doi.org/10.1029/2026JA035221

(a) Errors (OMNI minus Cluster-1) in the interplanetary magnetic field strength perpendicular to the Sun-Earth axis for all minutes in years 2001-2023. (b) Binned means and standard deviations of data in panel (a) and coefficients of fitted truncated Normal distributions (maximum likelihood estimates and 95% confidence intervals). (c) PDF of data in panel (a).