Enhanced tropical cyclone precipitation variability is linked to Pacific Decadal Oscillation since the 1940s
Bibliographic record
Abstract
Southeastern China is pivotal for understanding tropical cyclone (TC) behavior in the Northwest Pacific, the most active TC basin on Earth. However, short instrumental records limit our knowledge of past tropical cyclone precipitation (TCP) and its response to human-driven warming. Here we combine multi-year monitoring of xylem cell formation with a process-based tree growth model to demonstrate that latewood width in coastal conifers is an effective proxy for TCP. We build a latewood chronology from the western Taiwan Strait and reconstruct July-September TCP from 1846 to 2020, explaining 62.6% of observed variance. The reconstruction reveals a marked increase in interannual TCP variability since the 1940s, closely associated with enhanced variability of the Pacific Decadal Oscillation. This work provides physiological evidence linking TCP to intra-annual tree-ring dynamics and establishes tree rings as a proxy for high-resolution TC reconstructions and climate risk assessment across the Pacific Rim. Latewood width records from southeast China show that increased tropical cyclone precipitation variability is linked to stronger Pacific Decadal Oscillation variability since the 1940s, indicating tree-ring dynamics as a new proxy for Pacific Rim climate risk.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".