Observations of traveling ionospheric disturbances driven by gravity waves from sources in the upper and lower atmosphere
Bibliographic record
Abstract
Abstract. Traveling ionospheric disturbances (TIDs) are observed by the Super Dual Auroral Radar Network (SuperDARN), the Poker Flat Incoherent Scatter Radar (PFISR), the multipoint and multifrequency continuous Doppler sounders, and the GNSS total electron content (TEC) mapping technique. PFISR measures electron density altitude profiles, from which TIDs are obtained by a filtering method to remove background densities. SuperDARN observes the ionospheric convection at high latitudes and TIDs modulating the ground scatter power. The Doppler sounders at mid latitudes can determine TID propagation velocities and azimuths. The aim of this study is to attribute the observed TIDs to atmospheric gravity waves generated in the lower thermosphere at high latitudes, or gravity waves generated by mid-latitude tropospheric weather systems. The solar wind-magnetosphere-ionosphere-thermosphere coupling modulates the dayside ionospheric convection and currents that generate gravity waves driving equatorward propagating medium to large scale TIDs. The horizontal equivalent ionospheric currents are estimated from the ground-based magnetometer data using an inversion technique. At high latitudes, TIDs observed in the detrended TEC maps are dominated by equatorward TIDs pointing to auroral sources. At mid to low latitudes, the azimuths of TIDs vary, indicating sources in the troposphere. The cases of eastward to southeastward propagating TIDs that are observed in the detrended TEC maps and by the HF Doppler sounders in Czechia are attributed to gravity waves that were likely generated by geostrophic adjustment processes and shear instability in the intensifying low-pressure systems.
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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 | 0.001 |
| 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) | 0.001 | 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".