Investigating the Role of Geomagnetic Activity in Loss of Navigational Capability in the Swarm Satellite Mission
Bibliographic record
Abstract
The Swarm satellite mission, launched by the European Space Agency in 2013, investigates Earth's ionosphere using advanced onboard instruments, including GPS receivers capable of tracking signals from up to eight satellites simultaneously. Loss of navigational capability, defined as periods when fewer than four GPS satellites are tracked, poses significant challenges for precise positioning and mission operations. Before 2020, the frequency of these events was relatively low, with fewer than 200 occurrences for Swarm A and C, and fewer than 100 for Swarm B. After 2020, the number of events increased dramatically, exceeding 1,400 for Swarm A and C, and 400 for Swarm B. While geomagnetic activity directly affects high-latitude regions, less than 10% of these events occur in the high-latitude ionosphere, suggesting indirect influences of magnetic storms on other latitudes through associated phenomena. This study investigates the correlation between geomagnetic activity and loss of navigational capability, exploring whether geomagnetic indices and magnetic storms act as precursors or are unrelated to these events. The findings will provide insights into the interplay between space weather and satellite-based navigation, contributing to improved operational resilience in future satellite missions.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".