On the 630 nm red‐line pulsating aurora: Red‐line Emission Geospace Observatory observations and model simulations
Bibliographic record
Abstract
Abstract In this study, we present observations of red‐line (630 nm) pulsating auroras using the camera system of Red‐line Emission Geospace Observatory (REGO), during a geomagnetic storm interval. We also develop a time‐dependent model to simulate the 630 nm auroral pulsations in response to modulated precipitation inputs and compare the model outputs with REGO observations. Key results are as follows. (1) Notwithstanding the long radiative timescale of the 630 nm emission, red‐line auroras can still be modulated by pulsating electron precipitations and feature noticeable oscillations, which constitute the red‐line pulsating auroral phenomena. (2) In a majority of cases, the oscillation magnitude of red‐line pulsating auroras is substantially smaller than that of the concurrent pulsating auroras seen on Thermal Emission Imaging System whitelight images (generally dominated by 557.7 nm green‐line emissions). Under certain circumstances, e.g., when the characteristic energy of the precipitation is very high, some of the pulsating auroras may not show discernible imprints on red line. (3) The altitude range contributing most to the red‐line pulsating aurora is systematically lower than that of the steady‐state red‐line aurora, since the slower O( 1 D ) loss rate at higher altitudes tends to suppress the oscillation range of the 630 nm emission rate. (4) We find that some pulsating auroral patches are characterized by enhanced red‐to‐green color ratio during their on time, hinting that the percentage increase of the red‐line auroral component exceeds that of the green‐line auroral component for those patches. We suggest that those special patches might possibly be associated with lower energy (<1 keV) electron precipitations.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".