Long-distance HF radio waves propagation during the April 2023 geomagnetic storm by measurements in Antarctica, in Europe, and aboard RV Noosfera
Bibliographic record
Abstract
The paper aims at an experimental study of the mechanisms of long-distance high-frequency (HF) propagation and spatial and temporal variations of the ionospheric parameters during the first hours of a severe geomagnetic storm of April 23, 2023 by spatially separated measuring equipment located at the research vessel (RV) Noosfera, the Ukrainian Antarctic Akademik Vernadsky station (hereinafter Vernadsky), and the LOFAR observatory PL610 in Borowiec (Poland). High-frequency vertical and oblique sounding techniques of the ionosphere were used. Geospace measurements were carried out synchronously. During the first hours of the geomagnetic storm of April 23–24, 2023, unexpectedly well-correlated variations in the Doppler frequency shifts of HF signals emitted from Vernadsky were observed at the RV Noosfera and the PL610 station. Furthermore, variations in Doppler frequency shifts of HF signals strongly correlate with magnetic field records in Antarctica and Poland. Variations in the frequency of HF signal spectral components, distinguishable during storm conditions, are utilized to clarify the mechanism of long-distance HF propagation and estimate the vertical velocity of ionospheric layers. Signals of HF CHU time radio station (Canada) at 7850 and 14670 kHz were unexpectedly observed in all receiving sites. Most probably, the CHU station radio signals registered during the initial stage of the geomagnetic storm were scattered on the polar ovals’ ionospheric inhomogeneities and propagated further along the return (long arc of the great circle) paths. Redistribution of the ionospheric plasma during the geomagnetic storm leads to the formation of HF radio propagation channels absent under quiet conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".