Contribution of Changes in Sea Surface Temperature and Aerosol Loading to the Decreasing Precipitation Trend in Southern China
Bibliographic record
Abstract
Abstract The effects of increasing sea surface temperature (SST) and aerosol loading in a drought region in Southern China are studied using aerosol optical depth (AOD), low-level cloud cover (LCC), visibility, and precipitation from observed surface data; wind, temperature, specific humidity, and geopotential height from the NCEP–NCAR reanalysis fields; and SST from the NOAA archive data. The results show a warming of the SST in the South China Sea and the Indian Ocean, and a strengthening of the West Pacific Subtropical High (WPSH) in the early summer during the last 40 yr, with the high pressure system extending farther westward over the continent in Southern China. Because the early summer average temperature contrast between the land and ocean decreased, the southwesterly monsoon from the ocean onto mainland China weakened and a surface horizontal wind divergence anomaly occurred over Southern China stabilizing the boundary layer. Thus, less moisture was transported to Southern China, causing a drying trend. Despite this, surface observations show that AOD and LCC have increased, while visibility has decreased. Precipitation has decreased in this region in the early summer, consistent with both the second aerosol indirect effect (reduction in precipitation efficiency caused by the more numerous and smaller cloud droplets) and dynamically induced changes from convective to more stratiform clouds. The second aerosol indirect effect and increases in SST and greenhouse gases (GHG) were simulated separately with the ECHAM4 general circulation model (GCM). The GCM results suggest that both effects contribute to the changes in LCC and precipitation in the drought region in Southern China. The flooding trend in Eastern China, however, is more likely caused by strengthened convective precipitation associated with increases in SST and GHG.
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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 | 0.000 |
| 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 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".