Near-Surface Ozone Variations in East Asia during Boreal Summer
Bibliographic record
Abstract
This study examined the variability of near-surface (850 hPa) ozone during summer in East Asia using simulations from 12 models participating in the Chemistry–Climate Model Initiative (CCMI). The empirical orthogonal function (EOF) analysis of non-detrended ozone shows that the first (second) EOF mode is characterized by a monopole (dipole) structure that describe 83.3% (7.1%) of total variance. The corresponding the first principle component (PC1) time series exhibits a gradually increasing trend due to the rising anthropogenic emission, whereas PC2 shows interannual variation. To understand the drivers of this interannual variability, the detrended ozone is also analyzed. The two leading EOF patterns of detrended ozone, EOF1 and EOF2, explain 37.0% and 29.2% of the total variance, respectively. The regression results indicate that the positive ozone anomaly in East Asia associated with EOF1 is caused by the combination of net ozone production and transport from the upper atmosphere. In contrast, EOF2 is associated with the weakened western Pacific subtropical high during the La Niña decaying summer, which tends to decrease monsoon precipitation, thus increasing ozone concentration in China. Our results suggest that the El Niño-Southern Oscillation (ENSO) plays a key role in driving interannual variability in tropospheric ozone in East Asia.
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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 | 0.000 |
| 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) | 0.000 | 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".