Modeling Study on the Asymmetry of Positive and Negative Storm Surges along the Southeastern Coast of China
Bibliographic record
Abstract
In this paper, a three-dimensional storm surge model was developed based on the Finite Volume Community Ocean Model (FVCOM) by the hindcasts of four typhoon-induced storm surges (Chan-hom, Mireille, Herb, and Winnie). After model validation, a series of sensitivity experiments were conducted to explore the effects of key parameters in the wind and pressure field (forward speed, radius of maximum wind (RMW), inflow angle, and central pressure), typhoon path, wind intensity, and topography on the storm surge and surge asymmetry between sea level rise (positive surge) and fall (negative surge) along the southeastern coast of China (SCC). The model results show that lower central pressure and larger RMW could lead to stronger surge asymmetry. A larger inflow angle results in a stronger surge asymmetry. In addition, the path of Chan-hom is the most dangerous path type for the Zhoushan Archipelago area, and that of Winnie follows next. The model results also indicate that the non-linear interaction between wind field and pressure field tends to weaken the peak surge elevation. The effect of topography on storm surges indicates that the peak surge elevation and its occurrence time, as well as the surge asymmetry, increase with a decreasing slope along the SCC.
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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 | 0.000 |
| 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) | 0.000 | 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".