Long‐Term Evolution of The Surface Refractivity for Arctic Regions
Bibliographic record
Abstract
Abstract In this paper, local meteorological data for a period of 35 years (from 1979 to 2013) from Kuujuaq station have been used to calculate the surface refractivity, N (a link for the data is available in the acknowledgements), and to estimate the vertical refractivity gradient, dN1, in the lowest atmospheric layer above the ground. Monthly and yearly variations of the mean of N and dN1 are provided. The values obtained are compared with the corresponding values from the ITU maps. The long‐term trend of the surface refractivity is also investigated. The data demonstrate that the indices N and dN1 are subject to an evolution that may have significance in the context of climate change. Monthly means of N show an increasing departure from ITU‐R values since 1990. Yearly mean values of the dN1 show a progressive decrease over the period of study. Seasonal means of dN1 show a decrease over time, especially for summer. Such a trend may increase the occurrence of superrefraction. However, currently available ITU‐R recommendations for microwave link design assume a stationary climate, so there is a need for a new modeling approach.
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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 | 0.000 |
| 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 | 0.000 | 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 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".