Skip to content
DraconiticResearch
Search Sources API
203,234 studies31 sourcesUpdated 39 min ago
PreprintCC BY-NC-SA 4.0arXiv

Extreme, transient bursts of energy in the auroral ionosphere. I. Predictive radar tracking

Abstract

Three-metre Farley-Buneman irregularities observed by the \textsc{icebear} VHF radar organize into clusters whose apparent motion follows the electric field mapped from the magnetosphere. We track these clusters automatically: each is bounded by an α-shape at every time step, consecutive frames are associated by an optimal assignment combining shape overlap with a predicted displacement. Births, deaths, splits, and mergers are monitored, and each trajectory is reduced to per-segment velocities by piecewise linear regression. Tracked speeds are validated against in-situ ion drifts measured by DMSP F16 during two conjunctions in May 2021. Across four years of disturbed conditions, the speed distribution of 74,517 tracked clusters agrees with Swarm A cross-track ion drifts to within a factor of two in probability density for all speeds between 300 and 4000 m/s, and the radar-tracked speed distribution continues as a power law well beyond the noise limit imposed on Swarm by spacecraft attitude jitter. Binning by geomagnetic activity yields a parameterization of the field dispersion conditional on threshold exceedance, σ2 = 3.68 × 105 (SME/100 nT)0.353~m2 s−2, equivalent to 30 to 60 mV/m across the observed activity range, which supplies the amplitude statistics entering the variance term of height-integrated Joule dissipation. During the 10 May 2024 super-storm, on closed field lines equatorward of the dayside cusp, we retrieved an upper-tail sample of this distribution, finding a cluster moving at 11,240±660 m/s and implying a field of approximately 560 mV/m. Together with the unstable fraction of a space weather model's grid volume, our parameterization can in future close the sub-grid contribution to the storm-time heating budget in the auroral ionosphere.

Related

  1. Introduction to TREx‐ATM V2.0: A Versatile Model of Auroral Transport and Its Effects in the Ionosphere
    Jun Liang, E. Donovan, E. Spanswick +3
    Earth and Space SciencePeer-reviewedCC BY-NC-ND5 citedPlanetary science & exoplanetsOpenAlex
  2. Magnetic Topological Evolution and the Predictive Role of Winding-flux-based Masked PILs in Extreme Solar Flares from AR13664 and AR13842
    Prithish Halder, Sudheer K. Mishra, Abhishekh K. Srivastava +2
    arXivPreprintCC BY 4.0Full textInstrumentation & methodsSolar & stellar physicsarXiv
  3. Observing the Earth's Plasmasphere and Ionosphere From the Lunar Surface
    Claudio Cesaroni, Luca Spogli, Marco Guerra +6
    Geophysical Research LettersPeer-reviewedCC BY5 citedPlanetary science & exoplanetsOpenAlex
  4. Energy distributions of precipitating electrons in Jupiter's auroral regions from combined Juno/JADE and Juno/JEDI measurements
    B. Benmahi, V. Hue, N. André +17
    Astronomy & AstrophysicsPeer-reviewedPublisher termsSolar & stellar physicsCrossref
  5. Modeling the Nightside Martian Ionosphere: Structure, Composition, and Energetics
    Yanxing Liu, Shiqi Wu, Xiaoshu Wu +3
    The Astrophysical JournalPeer-reviewedCC BY 4.0Full textSolar & stellar physicsIOP/AASCrossref
BibTeX
@misc{ivarsen2026extreme,
  title = {{Extreme, transient bursts of energy in the auroral ionosphere. I. Predictive radar tracking}},
  author = {Magnus F Ivarsen and Jean-Pierre St-Maurice and Devin R Huyghebaert and Yukinaga Miyashita and Saif Marei and Jordan Cho and Mahith Madhanakumar and Megan Gillies and Dan Billett and Glenn C Hussey},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2605.31046},
  eprint = {2605.31046},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.31046},
  note = {CC BY-NC-SA 4.0},
}
RIS
TY  - UNPB
TI  - Extreme, transient bursts of energy in the auroral ionosphere. I. Predictive radar tracking
AU  - Magnus F Ivarsen
AU  - Jean-Pierre St-Maurice
AU  - Devin R Huyghebaert
AU  - Yukinaga Miyashita
AU  - Saif Marei
AU  - Jordan Cho
AU  - Mahith Madhanakumar
AU  - Megan Gillies
AU  - Dan Billett
AU  - Glenn C Hussey
PY  - 2026
DA  - 2026/09/11
PB  - arXiv
DO  - 10.48550/arxiv.2605.31046
UR  - https://arxiv.org/abs/2605.31046
AB  - Three-metre Farley-Buneman irregularities observed by the \textsc{icebear} VHF radar organize into clusters whose apparent motion follows the electric field mapped from the magnetosphere. We track these clusters automatically: each is bounded by an α-shape at every time step, consecutive frames are associated by an optimal assignment combining shape overlap with a predicted displacement. Births, deaths, splits, and mergers are monitored, and each trajectory is reduced to per-segment velocities by piecewise linear regression. Tracked speeds are validated against in-situ ion drifts measured by DMSP F16 during two conjunctions in May 2021. Across four years of disturbed conditions, the speed distribution of 74,517 tracked clusters agrees with Swarm A cross-track ion drifts to within a factor of two in probability density for all speeds between 300 and 4000 m/s, and the radar-tracked speed distribution continues as a power law well beyond the noise limit imposed on Swarm by spacecraft attitude jitter. Binning by geomagnetic activity yields a parameterization of the field dispersion conditional on threshold exceedance, σ^2 = 3.68 × 10^5 (SME/100 nT)^0.353~m^2 s^−2, equivalent to 30 to 60 mV/m across the observed activity range, which supplies the amplitude statistics entering the variance term of height-integrated Joule dissipation. During the 10 May 2024 super-storm, on closed field lines equatorward of the dayside cusp, we retrieved an upper-tail sample of this distribution, finding a cluster moving at 11,240±660 m/s and implying a field of approximately 560 mV/m. Together with the unstable fraction of a space weather model's grid volume, our parameterization can in future close the sub-grid contribution to the storm-time heating budget in the auroral ionosphere.
ER  -