An observational study of the inner core structure of Typhoon Meranti (2016) near landfall
Bibliographic record
Abstract
Abstract When passing by Taiwan, Typhoon Meranti (2016) was deflected northwards and shrank on infrared images, while its intensity maintained above 50 m⋅s–1 with the radius of maximum wind (RMW) smaller than 30 km. In this paper, satellite and ground‐based dual‐Doppler data were adopted to document Meranti's inner core evolution after its interaction with Taiwan's topography. It was found that the eyewall of Meranti was highly asymmetric on radar reflectivity with maximum on the down motion left side during its landfalling stage in Taiwan Strait, whereas the environmental vertical shear (about 3 m⋅s–1) was not favorable for asymmetry of this strength. As Meranti was very close to Taiwan's southern tip when passing by, its deep convection distribution, especially part on the down motion right side, was impaired by the topography of Central Mountain Range, thus contributed to this asymmetry. The eyewall at 1645 UTC was examined in detail, and it was found that the primary circulation with weaker azimuth perturbations remained intact at this time, while vertical circulation differed with direction. Besides, there was a low level northeast‐southwest flow through the eye, same as the direction of Taiwan Strait. Perhaps this radial inflow, along with the primary circulation, had contributed to the maintenance of asymmetry in reflectivity, so the eyewall did not recover in the Strait despite the weak wind shear. In addition, stronger storm‐relative wind asymmetry in the mid‐troposphere was observed. This wind asymmetry was in favor of track deflection, so was the diabatic heating associated the rainfall asymmetry. The channel wind, along with downslope wind from Taiwan, may help to maintain the intensity of Meranti and the smaller RMW, which needed further investigation with high resolution numerical models.
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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 | 0.000 |
| 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".