Real-time HF Radio Absorption Maps Incorporating Riometer and Satellite Measurements
Bibliographic record
Abstract
A real-time model of HF radio propagation conditions is being developed as a service for aircraft communications at high latitudes. An essential component of this is a real-time map of the absorption of HF (3-30 MHz) radio signals in the D-region ionosphere. Empirical, climatological Polar Cap Absorption (PCA) models in common usage cannot account for day-to-day variations in ionospheric composition and are inaccurate during the large changes in recombination rate at twilight. However, parameters of such models may be optimised using an age-weighted regression to absorption measurements from riometers in Canada and Scandinavia. Such parameters include the day- and night-time sensitivity to proton flux as measured on a geostationary satellite (GOES). Modelling the twilight transition as a linear or Gauss error function over a range of solar-zenith angles (χl < χ < χu) is found to provide greater accuracy than ‘Earth shadow’ methods (as applied in the Sodankylä Ionospheric Chemistry (SIC) model, for example) due to a more gradual ionospheric response for χ < 90°. The fitted χl parameter is found to be most variable, with smaller values (as low as 60°) post-sunrise compared with pre-sunset. Correlation coefficients of model parameters between riometers are presented and these provide a means of appropriately weighting individual riometer contributions in an assimilative PCA model. At times outside of PCA events, the probability of absorption in the auroral zones is related to the energetic electron flux inside the precipitation loss cone, as measured on the polar-orbiting POES satellites. This varies with magnetic local time, magnetic latitude and geomagnetic activity, and its relation to the real-time solar wind – magnetospheric coupling function [Newell et al., 2007] will be presented.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".