An evaluation of East Asian Extratropical cyclones in CMIP5 models and their response to greenhouse warming
Bibliographic record
Abstract
The extratropical cyclones (ETCs) over East Asia and their possible future changes are evaluated using the Coupled Model Intercomparison Project phase 5 (CMIP5) models. The East Asian ETCs are identified using an automated tracking algorithm applied to the 850-hPa relative vorticity field for both reference data (ERA-Interim reanalysis data) and model data. The CMIP5 models well capture the spatial distribution of East Asian ETC properties, although significant biases are present around the high-topography regions. Based on the individual model biases, Best 5 models are selected and used for examining the future changes of East Asian ETCs. In future climate, Best 5 shows declined cyclogenesis in the leeward side of the Tibetan Plateau, which is partly responsible for the decreased ETC frequency over the western North Pacific. The intensity of individual ETCs is also projected to decrease in a warm climate. These changes could be attributed to the combined effect of increased static stability and decreased vertical wind shear in East Asia, which means reduced local baroclinicity. It is also found that CMIP6 models have smaller bias than Best 5 CMIP5 models, indicating that the result documented in this study may change in quantity when newly-available CMIP6 models are utilized.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".