Poynting Flux Input to the Auroral Ionosphere: The Impact of Subauroral Polarization Streams and Dawnside Auroral Polarization Streams
Bibliographic record
Abstract
Abstract The Poynting vector (Poynting flux) from Earth's magnetosphere downward toward its ionosphere carries the energy that powers the Joule heating in the ionosphere and thermosphere. The Joule heating controls fundamental ionospheric properties affecting the entire magnetosphere‐ionosphere‐thermosphere system, so it is necessary to understand when and where the Poynting flux is significant. Taking advantage of new data sets generated from DMSP (Defense Meteorological Satellite Program) observations, we investigate the Poynting flux distribution within and around the auroral zone, where most magnetosphere‐ionosphere (M‐I) dynamics and thus Joule heating occurs. We find that the Poynting flux, which is generally larger under more active conditions, is concentrated in the sunlit cusp and near the interface between Region 1 and 2 currents. The former concentration suggests voltage generators drive the cusp dynamics. The latter concentration shows asymmetries with respect to the interface between the Region 1 and 2 currents. We show that these reflect the controlling impact of subauroral polarization streams and dawnside auroral polarization streams on the Poynting flux.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".