Contrasting aerosol trends over South Asia during the last decade based on MODIS observations
Bibliographic record
Abstract
Abstract. Atmospheric aerosols over south Asia constitute a major environmental and climate issue. Thus, extensive land and cruise campaigns have been conducted over the area focusing on investigating the aerosol properties and climate implications. Except from the ground-based instrumentation, several studies dealt with analyzing the aerosol properties from space, focusing mainly on the spatial distribution of the aerosol optical depth (AOD) and possible feedbacks of aerosols on the monsoon system. However, except from some works using ground-based instrumentation or satellite observations over a specific region, there is lack of studies dealing with monitoring of the aerosol trend over south Asia. The present work analyzes the variations and trends in aerosol load over south Asia using Terra-MODIS AOD550 data in the period 2000–2009. Overall, an increasing trend of 10.17 % in AOD is found over whole south Asia, which exhibits large spatio-temporal variation. More specifically, the AOD550 increasing trend is more pronounced in winter, and especially over northern India. The present study shows an evidence of a decreasing AOD550 trend over the densely-populated Indo-Gangetic Plains (IGP) during the period April–September, which has never been reported before. This decreasing trend is not statistically significant and leads to an AOD change of −0.01 per year in June, when the dust activity is at its maximum. The AOD decrease seems to be attributed to weakness of dust activity in the northwest of India, closely associated with expansion of the vegetated areas and increase in precipitation over the Thar desert. Similarly, GOCART simulations over south Asia show a pronounced decreasing trend in dust AOD in accordance with MODIS. However, much more analysis and longer dataset are required for establishing this evidence.
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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 | 0.000 | 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) | 0.011 | 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".