Abrupt Intensification and Dissipation of Tropical Cyclones in Indian Ocean: A Case Study of Tropical Cyclone Nilofar – 2014
Bibliographic record
Abstract
This study aims to investigate the possible influence of different atmospheric forcing on intensification/dissipation of tropical cyclonic “Nilofar” in Arabian Sea appeared during the last week of October, 2014 which exhibited abrupt intensification and dissipation as well. The cyclone was monitored by the Tropical Cyclone Warning Center (TCWC) of Pakistan Meteorological | department and the Regional Specialized Meteorological Center (RSMC) of Indian Meteorological | department (IMD) continuously, issued warnings and advisories with the help of available synoptic observations, satellite data and numerical models. Almost all the essential ingredients for intensification and tracking of the cyclone were studied and monitored accurately. Although the track forecast of the cyclone remained up to mark; but great errors occurred in intensity forecast. The atmospheric vertical wind shear could not be studied accurately. The intensity of wind shear itself is dependent on both; the local and global atmospheric forcing and climate variables, reoccurring periodically, especially while occurring two or more at the same time. More studies are required for influence of these climate variables while co-occurring at the same time period. This study will help weather forecasters to pay special attention on variation of climate factors affecting the wind shear for proper forecasting of tropical cyclones in the Arabian Sea for the safety of coastal communities along the coast.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".