Analysing present, past and future tropical cyclone activity as inferred from an ensemble of Coupled Global Climate Models
Bibliographic record
Abstract
Using the Yearly Genesis Parameter (YGP) and the Convective-YGP (CYGP), the main large-scale climatic fields controlling tropical cyclone (TC) formation are analysed and used to infer the number of TCs in a given basin using ERA40 reanalyses for the period 1983–2002. Both indices show a reasonable global number and spatial distribution of implied TCs compared to observations.Using the same approach, we evaluate TC activity in the last 20-yr period of the 20th century in an ensemble of nine Coupled Global Climate Model simulations submitted to the IPCC AR4. We extend this analysis backwards in time, through the 20th century, and find the ensemble derived CYGP suggests no trend in inferred TC numbers while the YGP, after applying a correction to compensate for its oversensitivity to sea surface temperature, suggests a small upward trend. Both indices give a fair geographical distribution of cyclogenesis. Finally, we assess future TC trends using three emission scenarios. Using the CYGP, which appears the most robust index for application to climate change, a small increase is predicted in the northwestern Pacific in the A1B and A2 scenarios.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".