Advancing Space Weather Hazard Research in Australia: A Journey of Discovery from AWAGS to AusLAMP
Bibliographic record
Abstract
A geomagnetic storm, also known as a geomagnetic disturbance (GMD), is a major disturbance of the Earth's magnetic field caused by solar activity. A geomagnetic storm induces electric currents in the Earth that feed into power lines through substation neutral earthing, causing instabilities and even blackouts in electricity transmission systems. The strength of geomagnetically induced currents (GICs) in the ground is directly related to the electrical conductivity of the surrounding geology. GICs experienced within power transmission lines are also influenced by the orientations and configuration of the power lines with respect to the electric fields. We installed a geoelectric field monitoring system at the Canberra geomagnetic observatory (CNB) to directly measure geomagnetically induced electric fields. This data enhances the capability in modelling and forecasting geoelectric hazards and can be used to validate the modelling approach through convolving magnetotelluric (MT) tensors with geomagnetic fields. In this presentation, we modelled the induced electric fields for the 1989 Quebec geomagnetic storm, using MT data collected at survey sites from the Australian Lithospheric Architecture Magnetotelluric Project. These results give us insight into the potential magnitude of space weather hazards to Australia's modern-day power grids. We extended this approach to a `Carrington-class' geomagnetic storm to evaluate geoelectric fields in the Australian region, allowing GICs flow in the power lines to be estimated. As an example, geomagnetically induced voltages in transmission lines from Queensland for a `Carrington-class' geomagnetic storm are presented.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".