Effect of Cyclone Track and Landfall Angle on the Magnitude of Storm Surges Along the Coast of Bangladesh in the Northern Bay of Bengal
Bibliographic record
Abstract
The position and configuration of the coastal shelf of the northern Bay of Bengal amplify the storm surge height extraordinarily. The low-lying coast of Bangladesh is severely devastated when extreme surges hit the land. However, the influence of track of a cyclone on surge height is not well known. A calibrated numerical model is used to simulate series of storm surges for a severe cyclone by shifting its track position and angle. The cyclonic wind field has been generated using the extreme parameters adopted from historical measurements. Surge heights simulated by the two-dimensional model are compared at selected locations along the coast. It was found that the cyclone with a landfall location at Barguna, a place between the Sundarban and the Meghna Estuary, develops the highest surge of 12.0 m (PWD) at the northeast of the estuary. The magnitude is further amplified to 13.0 m (PWD) when the surge coincides with the high-tide condition; a surge of similar magnitude attacked the coast of Bangladesh in 1876. Change in track orientation shows little influence on surge heights at the eastern coast. However, relatively higher effect was found in the western coast. Surge height distribution has also been presented with respect to local land or embankment elevation for the extreme event. A flood map is produced showing inundation depth in the aftermath of the extreme surge attack. The coastal areas at the northern tip of the upper bay and the western banks of the Meghna Estuary are found to be the most vulnerable locations.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".