Long-term trends in visibility and atmospheric extinction coefficient over Yunnan-Guizhou Plateau in southwest China for 1961-2006
Bibliographic record
Abstract
In this study on the regional climatic variability of visual range,atmospheric extinction coefficient (AEO) and haze episodes,we applied the data of visibility,precipitation,relative humidity,wind speed and weather phenomenon observed at 203 stations across the Yunnan-Guizhou Plateau (YGP) in Southwest China from 1961 to 2006.Long-term trends of the annual mean visibility and AEO were calculated as a linear tendency by using a linear regression model for each station.An analysis of the annual frequency of visibility 19 km,AEO and the annual days of haze was also performed with the Mann-Kendall test for detecting a significant trend with an abrupt change over the 46 years.It was found that the visibility of 84.2% stations decreased on the YGP with the negative trends from-11 to-1 km per 10 years,while the visibility at 15.8% stations increased mostly on the high level and sparsely-populated areas.An overall decline in the annual mean visibility from 34km in 1960s to about 27 km in the 21st century across the YGP was with the negative trends of-0.96 km/10yrs and-1.6 km/10yrs respectively during 1961—1979 and 1980—2006.The annual frequency of visibility19 km lessened at 71% stations over YGP with an averaged trend of-2% per year.The annual mean haze episodes rose on the east and central region of YGP.Using the Mann-Kendall test,the interannual changes in frequency of visibility19 km,haze episodes and AEO were characterized with the abrupt changes.The abrupt changes occurred during the 1970s and the1990s,respectively.The negative trend in visibility and the positive trend in AEO could result from the enhanced aerosol concentrations and atmospheric pollution over the YGP.
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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 | 0.001 | 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".