Dynamic Processes Dominating Ozone Variability in Warm Seasons of 2014–2018 over the Yangtze River Delta Region, China
Bibliographic record
Abstract
Abstract. Ozone (O3) pollution is of great concern in the Yangtze River Delta (YRD) region of China, and the regional O3 pollution is closely associated with dominant weather systems. With a focus on the warm seasons (April–September) from 2014 to 2018, we quantitatively analyze the characteristics of O3 variations over the YRD, the impacts of large-scale and synoptic-scale circulations on the variations and the associated meteorological controlling factors, based on observed ground-level O3 and meteorological data. Our analysis suggests an increasing trend of the regional mean O3 concentration in the YRD at 1.81 ppb per year over 2014–2018. Spatially, the empirical orthogonal function (EOF) analysis suggests the dominant mode accounting for 65.70 % variation in O3, implying that an increase in O3 is the dominant tendency in the entire YRD. Meteorology is estimated to increase the regional mean O3 concentration by 2.81 ppb at most from 2014 to 2018. Relative humidity is found to be the most influential meteorological factor impacting O3 concentration. As the atmospheric circulation can affect local meteorological factors and O3 levels, we identify five dominant synoptic weather patterns (SWPs) in the warm seasons in the YRD using the t-mode principal component analysis (PTT) classification. The typical weather systems of SWPs include western Pacific Subtropical High (WPSH) under SWP1, a continental high under SWP2, an extratropical cyclone under SWP3, a southern low pressure and WPSH under SWP4 and the north China anticyclone under SWP5. The annual variations of all five SWPs are favorable to the increase in O3 concentrations over 2014–2018. Moreover, the change in SWP intensity contributes more to the O3 inter-annual variation than the SWP frequency change. The SWP intensity change includes the weakening and northward-extending of the western Pacific subtropical high (WPSH) under SWP1, the weakening of the continental high under SWP2, an extratropical cyclone strengthening under SWP3, the southern low pressure weakening and WPSH weakening under SWP4, and the north China anticyclone weakening under SWP5. All these changes prevent the water vapor in the southern sea from being transported to the YRD, and increase air temperature in the YRD. In addition, the descending motions strengthen in the YRD located behind the trough and in front of the ridge due to the strengthening of the ridge and trough in the westerlies. Then, the strengthened descending motion leads to less cloud cover and strong solar radiation, which are favorable to O3 formation and accumulation. Finally, we reconstruct an EOF mode 1 time series that shows high correlation with the original O3 time series, and the reconstructed time series performs well in defining the change in SWP intensity according to the unique feature under each of the SWPs.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".