Ionospheric Scintillation Activity Over Canada in 2019–2023 and Its Potential Influence on Wide Area Augmentation System (WAAS) Navigation Services for Aviation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Ionospheric scintillation caused by space weather impacts the accuracy and availability of GNSS services and is considered a natural hazard for aviation and other GNSS users. Increased solar activity in 2021–2023, attributed to the ascending phase of the 25th solar cycle, caused an amplification of ionospheric disturbances including the intensity and duration of ionospheric scintillations. These disturbances affect the propagation of GNSS satellite signals and result in the degradation of both GNSS performance and the performance of GNSS augmentation systems. Events where ionospheric disturbances have a significant impact on navigation services for aviation are documented by Transport Canada's Civil Aviation Daily Occurrence Reporting System (CADORS). This paper analyzes scintillation activity from 2019 to 2023 over Canada using phase scintillation data provided by the Canadian High Arctic Ionospheric Network. Times when phase scintillation index exceeds 0.4 rad were used to evaluate the impact from scintillation activity on the availability of the Wide Area Augmentation System (WAAS) service and on related issues for aviation as recorded in CADORS. This analysis demonstrates a notable increase in the number of recorded aviation issues related to WAAS coverage during 2021–2023, coinciding with higher solar and scintillation activity. Analysis of CADORS reports related to periods of unavailability of WAAS precision approach services is included to demonstrate effects to aviation. This study highlights the critical impact of space weather on navigation services and the importance of monitoring and forecasting scintillation activity to ensure the reliability of GNSS‐dependent operations, especially in aviation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
| 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 it