A Vorticity‐Divergence View of Internal Wave Generation by a Fast‐Moving Tropical Cyclone: Insights From Super Typhoon Mangkhut
Bibliographic record
Abstract
Abstract Tropical cyclones (TCs) are powered by heat fluxes across the air‐sea interface, which are in turn influenced by subsurface physical processes that can modulate storm intensity. Here, we use data from 6 profiling floats to recreate 3D fields of temperature ( T ), salinity ( S ), and velocity around the fast‐moving Super Typhoon Mangkhut (western North Pacific, September 2018). Observational estimates of vorticity ( ζ ) and divergence (Γ) agree with output from a 3D coupled model, while their relation to vertical velocities is explained by a linear theoretical statement of inertial pumping. Under this framework, inertial pumping is described as a linear coupling between ζ and Γ, whose oscillations in quadrature cause periodic displacements in the ocean thermocline and generate near‐inertial waves (NIWs). Vertical profiles of T and S show gradual mixing of the upper ocean with diffusivities as high as κ ∼ 10 −1 m 2 s −1 , which caused an asymmetric cold wake of sea surface temperature (SST). We estimate that ∼10% of the energy used by mixing was used to mix rainfall, therefore inhibiting SST cooling. Lastly, watermass transformation analyses suggest that κ > 3 × 10 −3 m 2 s −1 above ∼110 m depth and up to 600 km behind the TC. These analyses provide an observational summary of the ocean response to fast‐moving TCs, demonstrate some advantages of ζ and Γ for the study of internal wave fields, and provide conceptual clarity on the mechanisms that lead to NIW generation by winds.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 teacher head, 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".