An Evaluation of Hurricane Superintensity in Axisymmetric Numerical Models
Bibliographic record
Abstract
Abstract Potential intensity (PI) is an analytical bound on steady, inviscid, axisymmetric hurricane wind speed. Studies have shown that simulated hurricane azimuthal wind speed can greatly exceed a PI bound on the maximum gradient wind. This disparity is called superintensity (SI) and has been attributed to the contribution of the unbalanced flow to the azimuthal wind. The goals of this study are 1) to introduce a new surface wind PI (PI s ), based on a differential Carnot cycle and bounding the magnitude of the surface winds; 2) to evaluate SI in numerical simulations with respect to diagnostic PI bounds on gradient wind (PI g ), azimuthal wind (PI a ), and surface wind (PI s ); and 3) to evaluate the validity of each PI bound based on the SI computations. Here, we define superintensity as the normalized amount by which each version of PI is exceeded by the quantity it bounds. Axisymmetric tropical cyclone simulations are performed while varying the parameterized turbulent mixing as a way of estimating SI in the inviscid limit. As the mixing length decreases, all three bounded wind speeds increase similarly from a sub-PI state to a marginally superintense state. This shows that all three forms of PI evaluated here are good approximations to their respective metrics in numerical simulations.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".