Secondary Circulation of Tropical Cyclones in Vertical Wind Shear: Lagrangian Diagnostic and Pathways of Environmental Interaction
Bibliographic record
Abstract
Abstract This study introduces a Lagrangian diagnostic of the secondary circulation of tropical cyclones (TCs), here defined by those trajectories that contribute to latent heat release in the region of high inertial stability of the TC core. This definition accounts for prominent asymmetries and transient flow features. Trajectories are mapped from the three-dimensional physical space to the (two dimensional) entropy–temperature space. The mass flux vector in this space subsumes the thermodynamic characteristics of the secondary circulation. The Lagrangian diagnostic is then employed to further analyze the impact of vertical wind shear on TCs in previously published idealized numerical experiments. One focus of this analysis is the classification and quantitative depiction of different pathways of environmental interaction based on thermodynamic properties of trajectories at initial and end times. Confirming results from previous work, vertical shear significantly increases the intrusion of low–equivalent potential temperature () air into the eyewall through the frictional inflow layer. In contrast to previous ideas, vertical shear decreases midlevel ventilation in these experiments. Consequently, the difference in eyewall between the no-shear and shear experiments is largest at low levels. Vertical shear, however, significantly increases detrainment from the eyewall and modifies the thermodynamic signature of the outflow layer. Finally, vertical shear promotes the occurrence of a novel class of trajectories that has not been described previously. These trajectories lose entropy at cold temperatures by detraining from the outflow layer and subsequently warm by 10–15 K. Further work is needed to investigate in more detail the relative importance of the different pathways for TC intensity change and to extend this study to real atmospheric TCs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".