An Ionospheric Warning and Alert System for the Canadian Coast Guard DGPS Service
Bibliographic record
Abstract
Under normal operating conditions DGPS positioning accuracies on the order of several metres are achieved in the Canadian sector. Such accuracies are well within the error bounds of 10 m (95%) specified by the Canadian Coast Guard. Under high levels of ionospheric activity, however, significant degradations in DGPS positioning accuracies can occur. Marine DGPS operations in Canada are particularly susceptible to such effects, where high latitude geomagnetic storms result in the aurora borealis (“Northern Lights”). During such events large differential ionospheric range errors can occur in and near the auroral region, leading to degradation of DGPS positioning results by a factor of two or more. A further effect associated with such storm events are phase and amplitude scintillations. During periods of intense scintillation amplitude fades can persist, resulting in the loss of GPS tracking and navigation capabilities. These storm-related effects tend to peak in the years following solar maximum, and may be a significant concern over the next few years (2002-2003). In order to provide timely predictions of such storm events, and associated degradations in positioning accuracies, we have recently investigated the feasibility of providing an ionospheric warning and alert system for Canadian Coast Guard DGPS users. Predictive capabilities are based on space weather parameters provided by the United States Space Environment Center at NOAA. These parameters are used to identify the nature of storm events and ionospheric phenomena in the auroral region. The impact of ionospheric activity on DGPS positioning accuracies has been quantified using three years of data from Canadian GPS reference stations. We have established strong correlations between DGPS performance and various ionospheric phenomena, and we have developed capabilities to provide predictions of degraded DGPS performance many hours in advance. While this system would be designed primarily for DGPS users in the Canadian sector, this method may also be extended for users in the Northern United States and Europe. This paper focuses on preliminary research recently conducted to develop the warning capabilities. Further testing and development is required for operational implementation.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 | 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 teacher head, 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".