Long-Term Effect of Barotropic Instability across the Moat in Double-Eyewall Tropical Cyclone–Like Vortices in Forced and Unforced Shallow-Water Models
Bibliographic record
Abstract
Abstract Secondary eyewall formation and the ensuing eyewall replacement cycles may take place in mature tropical cyclones (TCs) during part of their lifetime. A better understanding of the underlying dynamics is beneficial to improving the prediction of TC intensity and structure. Previous studies suggested that the barotropic instability (BI) across the moat (aka type-2 BI) can make a substantial contribution to the inner-eyewall decay through the associated eddy radial transport of absolute angular momentum (AAM). Simultaneously, the type-2 BI can also increase the AAM of the outer eyewall. While the previous studies focused on the early stage of the type-2 BI, this paper explores the long-term effect of the type-2 BI and the underlying processes in forced and unforced shallow-water experiments. Under the long-term effect, it will be shown that the inner eyewalls repeatedly weaken and strengthen (while the order is reversed for the outer eyewalls). Sensitivity tests are conducted to examine the sensitivity of the long-term effect of the type-2 BI to different vortex parameters and the strength of the parameterized diabatic heating. Implication of the long-term effect for the intensity changes of the inner and outer eyewalls of real TCs are also discussed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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".