The Solar Flux Dependence of Ionospheric 150 km Radar Echoes and Implications
Bibliographic record
Abstract
Abstract Radar echoes from the daytime equatorial ionospheric F1 region, popularly known as “150 km echoes,” have challenged ionospheric plasma physicists for several decades. Recent theoretical simulations showed that enhanced photoelectron fluxes can amplify the amplitude of plasma waves, generating spectra similar to those of the radar echoes, implying that larger solar fluxes should produce more frequent and stronger 150 km echoes. Inspired by this proposal, we studied the occurrence and intensity dependence of the echoes on the EUV flux observed by SOHO over several years. The occurrence and intensity of the echoes were found to have an inverse relationship with this EUV flux measurement. The multiyear trend is independent of the variability often observed over successive days with nearly identical EUV fluxes. These results imply that the relationship between the echoes and EUV flux is more complex. We propose that gravity waves modulate the amplitude of 150 km echoes through changes in the variations in plasma density and photoelectron fluxes associated with the gravity wave‐induced neutral density modulations.
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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".