The Footprint of Atlantic Multidecadal Oscillation on the Intensity of Tropical Cyclones Over the Western North Pacific
Bibliographic record
Abstract
Sea surface temperature (SST) over the western North Pacific (WNP) exhibits strong decadal to multidecadal variability and in this region, warm waters fuel the tropical cyclones (TCs). Observational records show pronounced decadal variations in WNP TC metrics during 1950–2018. Statistical analysis of the various TC metrics suggests that the annual average intensity of WNP TCs is closely linked to the AMO (r = 0.86 at decadal timescales, p < 0.05). Observations and coupled atmosphere-ocean simulations show that the decadal WNP SST variations regarded as the primary driver of TC intensity, are remotely controlled by the AMO. Corresponding to the WNP SST warming, the local SLP gets lower and the tropospheric air becomes warmer and moister, enhancing atmospheric instability and the generation of convective available potential energy. These favorable changes in the background environment provide more “fuel” to the development of deep convection and intensify the WNP TCs. The footprints of AMO in WNP SST and atmospheric states through trans-basin interaction eventually exert a significant impact on the TC intensity over the WNP region.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".