Altitude Distribution of Large and Small‐Scale Equatorial Ionospheric Irregularities Sampled From an Elliptical Low‐Earth Orbit
Bibliographic record
Abstract
Abstract We provide insight into the vertical distribution of multi‐scale scintillation‐inducing irregularities in the low‐latitude ionosphere. In four sets of novel experiments, we sampled altitudes from 330 to 1,280 km in the 18–24 magnetic local time (MLT) sector using the Swarm Echo GPS Attitude, Positioning, and Profiling Experiment occultation receiver (GAP‐O) GPS receiver with its antenna oriented toward zenith. In order to identify multi‐scale irregularities both above and at the satellite's position, we utilize high‐sample‐rate GAP‐O amplitude and phase measurements along with a measurement of net current on the surface of the imaging and rapid‐scanning ion mass spectrometer sensor on board, which serves as a proxy for density variations. By calculating the rate of change of total electron content index using two sets of GPS parameter choices, we are able to sample irregularities as small as 160 m, which is comparable to or smaller than the Fresnel scale responsible for scintillation‐inducing irregularities. During one campaign, we find that amplitude scintillations on the GPS signal coincide with strong in‐situ small‐scale density irregularities in 32% of cases, indicative of a broad irregularity region extending from the satellite's position to hundreds of kilometers above. Also, we show that large‐scale ionospheric disturbances (larger than 80 km) occur predominantly below 500 km, and down to the 330 km perigee of Swarm Echo in the 18–21 MLT sector. In contrast, small‐scale variations of total electron content are detected at all MLTs between 18 MLT and magnetic midnight and at all altitudes sampled in this experiment. However, they are more frequent in the 22–24 MLT range.
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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 | 0.001 |
| 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 | 0.000 | 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".