Obtaining Continental‐Scale, High‐Resolution 2‐D Ionospheric Flows and Application to Meso‐Scale Flow Science
Bibliographic record
Abstract
Abstract An approach for creating continental‐scale, multi‐scale plasma convection maps in the nightside high‐latitude ionosphere using the spherical elementary current systems technique has been developed and evaluated. The capability to reconstruct meso‐scale flow channels improved dramatically, and the velocity errors were reduced by ∼30% compared to the spherical harmonic fitting method. Uncertainties of velocity vectors estimated by varying the model setup was also low. Convection maps for a substorm event revealed multiple flow channels in the polar cap, dominating the convection in the quiet time and early growth phase. The meso‐scale flows extended toward the nightside auroral oval and had continuous flow channels over >20° of latitude, and the flow channels dynamically merged and bifurcated. The substorm onset occurred along one of the flow channels, and the azimuthal extent of the enhanced flows coincided with the initial width of the auroral breakup. During the expansion phase, the meso‐scale flows repetitively crossed the oval poleward boundary, and some of them contributed to subauroral polarization streams enhancements. Increased flows extended duskward, along with the westward traveling surge. Then, flows near midnight weakened and evolved to the Harang flow shear. The meso‐scale flow channels had significant (∼10%–40% on average) contributions to the total plasma transport. The meso‐scale flows were highly variable on ∼10 min time scales and their individual maximum contributions reached upto 73%. These results demonstrate the capability of specifying realistic convection patterns, quantifying the contribution of meso‐scale transport, and evaluating the relationship between meso‐scale flows and localized auroral forms.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".