The Martian Ionospheric Response to the Co‐Rotating Interaction Region That Caused the Disappearing Solar Wind Event at Mars
Bibliographic record
Abstract
Abstract An unusually low density solar wind event was observed in December 2022 moving past both Earth and Mars. The source was traced back to a coronal hole and active region on the Sun's surface. The resulting solar wind lead to the development of a co‐rotating interaction region (CIR) and trailing rarefaction region that lasted for multiple solar rotations. Within this structure, the solar wind conditions, including density, velocity, and magnetic field magnitude and orientation drastically changed. In this study we analyze the response of the Martian ionosphere using MAVEN data to these changing solar wind conditions. The low density solar wind region associated with the December event resulted in the expansion of the Martian ionospheric boundaries. We show that the ion composition boundary (ICB) is located at extreme altitudes that are beyond previously observed locations from the MAVEN mission between 2015 and 2018. Furthermore, the boundary between shocked solar wind and the Martian ionosphere identified using electron and ion data moved together on the dayside of the planet with the changing solar wind conditions. However, at the flank region these boundaries do not move together, and we show here that the decoupling of the two boundaries may be the result of a change in the interplanetary magnetic field azimuthal angle.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".