Probing of medium-scale traveling ionospheric disturbances using HF-induced scatter targets
Bibliographic record
Abstract
Abstract. Experimental results from the Tromsø and Sura heating experiments at high and mid-latitudes are examined. It is shown that the combination of HF-induced target and bi-static HF Doppler radio scatter observations is a profitable method for probing medium-scale traveling ionospheric disturbances (TIDs) at high and mid-latitudes. HF ionospheric modification experiments provide a way of producing the HF-induced scatter target in a controlled manner at altitudes where the sensitivity to TIDs is highest. Bi-static HF Doppler radio scatter observations were carried out on the London-Tromsø-St. Petersburg path in the course of a Tromsø heating experiment on 16 November 2004 when the pump wave was reflected from an auroral Es-layer. During Sura heating experiments on 19 and 20 August 2004, when the HF pump wave was reflected from the F2 ionospheric layer, multi-position bi-static HF Doppler radio scatter observations were simultaneously performed at three reception points including St. Petersburg, Kharkov, and Rostov-on-Don. Ray tracing and Doppler shift simulations were made for all experiments. A computational technique has been developed allowing the reconstruction of the TID phase velocities from multi-position bi-static HF Doppler scatters. Parameters of medium-scale TIDs were found. In all experiments they were observed in the evening and pre-midnight hours. TIDs in the auroral E-region with periods of about 23 min were traveling southward at speeds of 210 m/s. TIDs in the mid-latitudinal F-region with periods from 20 to 45 min travelled at speeds between 40 and 150 m/s. During quiet magnetic conditions the waves were traveling in the north-east direction. In disturbed conditions the waves were moving in the south-west direction with higher speeds as compared with quiet conditions. Possible sources for the atmospheric gravity waves at middle and high latitudes are discussed.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".