Preliminary results on the sensitivity of atmospheric bending angles retrieved from COSMIC radio occultations to Doppler frequency shift and satellite velocity variationsThis article is one of a series of papers published in this Special Issue on the theme <i>GEODESY</i>.
Bibliographic record
Abstract
We describe and present preliminary results from an independent bending-angle algorithm implementation for the calculation of radiowave bending angles propagated from a Global Positioning System (GPS) to a Low Earth Orbiting (LEO) satellite. The algorithm utilizes raw atmospheric excess phases and satellite kinematics to determine Doppler frequency shifts of the GPS signals from which bending-angle profiles are derived. The intent is twofold: (a) perform a series of sensitivity studies to investigate the effect of Doppler frequency shift and satellite velocity variations on bending-angle profiles; and (b) examine and compare our results against the bending-angle profiles provided by the Constellation Observing System for Meteorology, Ionosphere & Climate (COSMIC) Data Analysis and Archive Centre (CDAAC). In this paper, we employ the same GPS observations as by CDAAC to analyze various occultation events in 2006, 2007, 2008, and 2009. Our principal finding is that radiowave bending angles exhibit an inversely proportional behaviour to orbital velocity variations while they change proportionally to the variations of Doppler frequency shift. Our studies also reveal that bending angles are more sensitive to orbital velocity than to Doppler frequency shift variations and show “wave-like” structures in the upper part of the atmosphere, unlike COSMIC-derived profiles. We discuss the differences between our derived bending-angle profiles and the COSMIC-derived profiles, emphasizing the advantages of our algorithm implementation.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".