Anthropogenic influence on the frequency of extreme temperatures in China
Bibliographic record
Abstract
Abstract Anthropogenic influence on the frequencies of warm days, cold days, warm nights, and cold nights are detected in the observations of Chinese temperature data covering 1958–2002. We used an optimal fingerprinting method to compare these temperature indices computed from a newly homogenized observational data set with those from simulations conducted with multiple climate models that participated in the Coupled Model Intercomparison Project Phase 5. We found the clear anthropogenic signals in the observational records of frequency changes in warm and cold days and nights. We also found that the models appear to be doing a better job in simulating the observed frequencies of daytime extremes than nighttime extremes. The model‐simulated variability appears to be consistent with that of the observations, providing confidence on the detection results. Additionally, the anthropogenic signal can be clearly detected at subnational scales, with detectable human influence found in Eastern and Western China separately.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".