Some aspects of the problem of secondary eyewall formation in idealized three‐dimensional nonlinear simulations
Bibliographic record
Abstract
Abstract Some aspects of the problem of secondary eyewall formation (SEF) are investigated with the aid of an idealized model. A series of experiments are conducted, starting with a strong annular vortex embedded in a quiescent background flow and forced by the sustained heating associated with a spiral rainband (control experiment). Following this, two experiments are configured to assess the impact of vertical wind shear (VWS) in the SEF process. The importance of the boundary layer force imbalance is finally investigated in a number of simulations in which surface and boundary layer physics are included. From the control experiment, it is found that in the absence of background environmental flow, the sustained latent heating associated with a spiral rainband can form a secondary eyewall even in the absence of a frictional boundary layer. The presence of VWS acts negatively in the SEF process by disrupting the organization of the potential vorticity induced by the rainband. When boundary layer physics is included, some similarities with previous studies are seen, but there is no SEF. These results suggest that the boundary layer most likely contributes to, rather than initiate, a secondary eyewall.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".