An investigation on how inner‐core structures obtained through radar data assimilation affect track forecasting of typhoon Jangmi (2008) near Taiwan Island
Bibliographic record
Abstract
Abstract The impacts of radar data assimilation (DA) on the westward track deflection of Typhoon Jangmi (2008) near Taiwan Island and the deflection mechanism are investigated. Initial conditions from two data assimilation experiments with significant track forecast differences are analyzed and compared. The environmental, axisymmetric, wave number 1 to 3 asymmetric fields of the typhoon are decomposed by using vortex separation and Fourier decomposition methods. The components are selectively recomposed into new initial conditions that include different vortex‐scale components to examine the impact of individual components on the track prediction. The wave number 1 asymmetric structure is found to play a dominant role in the westward deflection of Typhoon Jangmi, and the accurate analysis of this component with radar DA helps to improve the track forecast. The wave number 1 asymmetric circulation is manifested as a pair of cyclonic and anticyclonic gyres with well‐defined ventilation flows through the inner‐core region, which provides additional steering of the typhoon vortex. The layer‐mean environmental steering flow and ventilation flow associated with the wave number 1 gyres are further calculated to quantitatively evaluate the impact of ventilation flow. The ventilation flow is shown to be responsible for most of the westward motion component, suggesting again its role in causing the westward track deflection of Typhoon Jangmi. The results also suggest the importance of analyzing vortex‐scale asymmetric structures for accurate tropical cyclone track forecasting, especially when there is a significant track deflection.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 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".