A Statistical Study of Nighttime Ionospheric NmF2 Enhancement at Middle‐to‐High Latitudes in the Northern Hemisphere
Bibliographic record
Abstract
Abstract The electron density in the ionosphere usually continuously decreases during nighttime due to the vanishing of sunlit ionization. However, it sometimes increases unexpectedly, which has been called nighttime ionospheric enhancement. Previous researches studied this type of phenomenon mainly in the low‐to‐middle latitude regions. Here, we investigate the nighttime ionospheric NmF2 enhancement at middle‐to‐high latitudes in the northern hemisphere (NH) during solar cycles 23–24 by analyzing the ionosonde observations at Chilton (51.1°N, 359.4°E, geomagnetic 48.5°N), Juliusruh (54.6°N, 13.4°E, 51.7°N), Tromsø (69.9°N, 19.6°E, 66.9°N), and Qaanaaq (77.5°N, 290.8°E, 84.3°N), as well as comparing with the Empirical Canadian High Arctic Ionospheric Model (E‐CHAIM). The observations show that the nighttime NmF2 enhancement occurs mainly in the winter solstice months (November–February), and the occurrence rate and relative amplitude of the enhancement are inversely related to solar activity. The observed results are in good agreement with the results obtained from E‐CHAIM. Furthermore, the model shows the spatial distribution of the enhancement at the middle‐to‐high latitudes in NH in winter, most obvious in geomagnetic latitude between 50°N and 65°N, and have longitudinal minima centered at 30°W and maxima centered at 120°W and 75°E. From these results, this unique phenomenon at middle latitude is explained probably by the plasma flux from the higher altitudes (e.g., topside ionosphere and plasmasphere) diffusing downward into the ionospheric F2 layer. However, at polar regions, under the influence of the abundant high‐density structures such as polar cap patches, auroral blob, particle precipitation, etc., the F region plasma density enhancement becomes more complicated.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".