Predictive Skill and Predictability of North Atlantic Tropical Cyclogenesis in Different Synoptic Flow Regimes
Bibliographic record
Abstract
Practical predictability of tropical cyclogenesis over the North Atlantic is evaluated in different synoptic flow regimes using the NCEP Global Ensemble Forecast System (GEFS) reforecasts with forecast lead time up to two weeks. Synoptic flow regimes are represented by tropical cyclogenesis pathways defined in a previous study based on the low-level baroclinicity and upper-level forcing of the genesis environmental state, including nonbaroclinic, low-level baroclinic, trough-induced, weak tropical transition (TT), and strong TT pathways. It is found that the strong TT and weak TT pathways have lower predictability than the other pathways, linked to the lower predictability of vertical wind shear and midlevel humidity in the genesis vicinity of a developing TT storm. Further analysis suggests that stronger extratropical influences contribute to lower genesis predictability. It is also shown that the regional and seasonal variations of the genesis predictive skill in the GEFS can be largely explained by the relative frequency of occurrence of each pathway and the predictability differences among pathways. Predictability of tropical cyclogenesis is further discussed using the concept of the genesis potential index.
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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 | 0.001 | 0.003 |
| 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 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".