Coupled Aerosol-Cloud Systems over Northern Vietnam during 7-SEAS/BASELInE: A Radar and Modeling Perspective
Bibliographic record
Abstract
The 2013 7-SEAS/BASELInE campaign over northern Southeast Asia (SEA) provided, for the first time ever, comprehensive ground-based W-band radar measurements of the low-level stratocumulus (Sc) systems that often exist during the spring over northern Vietnam in the presence of biomass-burning aerosols. Although spatially limited, ground-based remote sensing observations are generally free of the surface contamination and signal attenuation effects that often hinder space-borne measurements of these low-level cloud systems. Such observations permit detailed measurements of structures and lifecycles of these clouds as part of a broader effort to study potential impacts of these coupled aerosol-cloud systems on local and regional weather and air quality. Introductory analyses of the W-band radar data show these Sc systems generally follow a diurnal cycle, with peak occurrences during the nighttime and early morning hours, often accompanied by light precipitation. Preliminary results from idealized simulations of Sc development over land based on the observations reveal the familiar response of increased numbers and smaller sizes of cloud droplets, along with suppressed drizzle formation, as aerosol concentrations increase. Slight reductions in simulated W-band reflectivity values also are seen with increasing aerosol concentrations and result primarily from decreased droplet sizes. As precipitation can play a large role in removing aerosol from the atmosphere, and thereby improving air quality locally, quantifying feedbacks between aerosols and cloud systems over this region are essential, particularly given the negative impacts of biomass burning on human health in SEA. Such an endeavor should involve improved modeling capabilities along with comprehensive measurements of time-dependent aerosol and cloud profiles.
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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 | 0.003 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".