The role of entrainment in axisymmetric tropical cyclones
Bibliographic record
Abstract
The intensification of tropical cyclones (TCs) results from the transport of conserved angular momentum, at least in an axisymmetric context. While there is general agreement on the role of moist cloud convection in driving the system, its precise contribution to intensification remains unclear. Additionally, the mechanisms by which convection facilitates angular momentum transport are still not well understood.Two prominent but seemingly contradictory explanations for this phenomenon exist in the literature: the Conditional Instability of the Second Kind (CISK) and Wind-Induced Surface Heat Exchange (WISHE). Although these models offer different perspectives, we propose that they represent limiting, asymptotic scaling regimes of the same underlying physical process.To reconcile these differing views, we use matched asymptotics to combine the three distinct regimes suggested by CISK and WISHE, thus providing a unified framework. Our analysis shows that the transport of angular momentum plays a crucial role in ensuring consistency with the asymptotic matching principle.Interestingly, this work uncovers a new, previously undocumented pathway for angular momentum transport that may serve as a plausible mechanism for TC intensification. A key element of this process is the special role of the top-of-boundary-layer (BL) inflow, which is closely linked to the entrainment of convective cloud towers.Through this combined approach, we offer a fresh perspective on TC intensification dynamics, confirming the validity of CISK and WISHE within their respective scopes and reconciling them into a more general theory.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".