Recent increase in the potential threat of western North Pacific tropical cyclones
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Conventionally, the threat of tropical cyclones (TCs) is often described by TC intensity. However, the damage caused by TCs is also strongly related to our forecasting ability, which is usually low for TCs with high intensification rates. Here, we challenge this intensity-only criterion and propose a concept of TC potential threat (PT) for the western North Pacific TCs by jointly clustering the TC lifetime maximum intensity and intensification rate. We show that TCs can be separated via an objective algorithm, and approximately 10% of all TCs pose a great PT and feature high forecast errors. Furthermore, the annual number of TCs with high PT has increased by 22% per decade over the past 41 years, and this trend is attributed to the rise in subsurface ocean temperatures. Our study provides a perspective on the TC threat and reveals its increase due to global warming and internal climate variability.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it