Comparative study of polar cap electron density measurements and E-CHAIM modeling
Bibliographic record
Abstract
The electron density in the Earth’s topside ionosphere has been studied with ground-based\nincoherent scatter radars (ISRs), Langmuir Probes (LP) placed on low-altitude satellites\nand many other instruments and techniques. These measurements have been continuously\ndigested into statistical models of the electron density distribution. These models are used for\nforecasting of radio wave propagation in the ionosphere. The success of ionospheric models\ndepends on the overall coverage by instruments and quality of their measurements. Joint\nobservations with multiple instruments, however, have been rarely considered while it is\nimportant to assess whether they report consistently comparable values of the electron density.\nOne example of a concern is an early suspicion in the LP experimentation in space that\nan underestimation effect can occur because of the contamination of the current-collecting\nsurfaces.\nThis thesis addresses several aspects of the electron density measurements in the ionosphere\nwith two instruments, ISRs and LP instruments onboard Swarm satellites, and modelling\nwith the recently developed Empirical Canadian High Arctic Ionospheric Model (E-CHAIM).\nThe study focuses on the Resolute Bay (Nunavut, Canada) area, located at extreme high\nlatitudes where the ionosphere is very dynamic and poorly investigated.\nThe first objective of the work was to evaluate the consistency of LP instruments on the\nSwarm A and C satellites flying one after another at the same altitude with a time separation\nof 7-10 seconds and spatial separation of ∼100 km. Occasional inconsistencies between the\nreported values were identified, and those were related to the occurrence of patches with\nenhanced electron density (polar cap patches). It was concluded that the polar cap patches\nare more frequent in the night sector, especially in summer and winter.\nSecondly, the long-term trends in the electron density reported by the satellites at two\nflight heights of ∼450 km (Swarm A and C) and ∼510 km (Swarm B) were investigated. A\nstrong solar cycle effect was identified, in agreement with predictions by the E-CHAIM model.\nComparison of the model output with the Swarm data showed typically larger values, up to\n30%.\nTo further assess the electron densities measured by the Swarm LP instruments, a point-\nby-point comparison with ISR measurements of the electron density was performed for about\n200 conjunction points. It was shown that Swarm values are lower than those measured by\nthe radars by ∼35%, on average. The agreement between the satellite-radar data is better for\nthe electron densities between 5×10^10 m−3 and 40×10^10 m−3 . The conclusion on the electron\ndensity underestimation for Swarm LP instruments is, overall, consistent with that reported\nfor middle latitudes in the past, but the effect is much stronger at high latitudes. Moreover, at high latitudes, the underestimation effect becomes progressively stronger as the electron\ndensity increases.\nFinally, predictions of the E-CHAIM model electron densities over Resolute Bay were\ncompared with measurements by the ISR radars with the goal of assessing the quality of model\npredictions at various heights. It was shown that for the middle part of the F layer, around\nits maximum, E-CHAIM shows reasonable agreement with measurements. The ratio of the\npredicted density to the observed density was mostly between 0.5 and 1.5, with 1.0 indicating\nperfect agreement. The best agreement was found in the summer. At the topside altitudes,\nthe model was found to underestimate electron densities, particularly in the summer season.\nThe worst agreement between the model and measurements was found for the ionospheric\nbottomside where the model often shows 2-3 times larger electron densities, especially in\nwinter and spring.\nAt the end of the thesis, suggestions for future research have been outlined.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".