Solar radio emission as a disturbance of aeronautical radionavigation
Bibliographic record
Abstract
On November 4th, 2015 secondary air traffic control radar was strongly disturbed in Sweden and some other European countries. The disturbances occurred when the radar antennas were pointing at the Sun. In this paper, we show that the disturbances coincided with the time of peaks of an exceptionally strong (∼105 Solar Flux Units) solar radio burst in a relatively narrow frequency range around 1 GHz. This indicates that this radio burst is the most probable space weather candidate for explaining the radar disturbances. The dynamic radio spectrum shows that the high flux densities are not due to synchrotron emission of energetic electrons, but to coherent emission processes, which produce a large variety of rapidly varying short bursts (such as pulsations, fiber bursts, and zebra patterns). The radio burst occurs outside the impulsive phase of the associated flare, about 30 min after the soft X-ray peak, and it is temporarily associated with fast evolving activity occurring in strong solar magnetic fields. While the relationship with strong magnetic fields and the coherent spectral nature of the radio burst provide hints towards the physical processes which generate such disturbances, we have so far no means to forecast them. Well-calibrated monitoring instruments of whole Sun radio fluxes covering the UHF band could at least provide a real-time identification of the origin of such disturbances, which reports in the literature show to also affect GPS signal reception.
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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 | 0.000 | 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".