The Limits of Empirical Electron Density Modeling: Examining the Capacity of E‐CHAIM and the IRI for Modeling Intermediate (1‐ to 30‐Day) Timescales at High Latitudes
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Bibliographic record
Abstract
Abstract The Empirical Canadian High Arctic Ionospheric Model (E‐CHAIM) is a new empirical 3‐D electron density model intended as an alternative to the use of conventional standards, such as the International Reference Ionosphere (IRI), at high latitudes (above 50°N). In this study, we have manually scaled a year of data from two Canadian High Arctic Ionospheric Network (CHAIN) ionosondes. Using this high‐quality data, we examine the behavior of the polar cap ionosphere under disturbed geomagnetic conditions and assess the capacity of E‐CHAIM to model polar cap F2‐peak electron density variability on “weather‐like,” intermediate timescales (1–30 days). This is a particularly challenging environment for monthly median empirical models due to the regular occurrence of variations about the monthly mean of up to 2 MHz. We demonstrate in this study that E‐CHAIM's storm model is capable of explaining 4 to 25% of polar cap foF2 variance at 1‐ to 30‐day timescales and 5 to 50% of the amplitude of that variability, while the IRI's Storm‐Time Ionospheric Correction Model (STORM) only explains 0.2 to 9% of the variance at these timescales and no more than 5% of their amplitude. While the IRI's STORM model provided no measurable improvement over the monthly median, E‐CHAIM's storm parameterization was able to improve overall root‐mean‐square errors by 0.05 to 0.1 MHz over its quiet time model. The overall improvement through the use of storm foF2 parameterizations is found to be limited, but measurable, particularly during storm periods, where an average improvement in root‐mean‐square error of 20% is observed.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it