Mechanisms for the intraseasonal variability of tropospheric ozone over the Indian Ocean during the winter monsoon
Bibliographic record
Abstract
We synthesize daily sonde (vertical) information and daily satellite (horizontal) information to provide an empirical description of ozone origins over the northern Indian Ocean during the INDOEX (Indian Ocean Experiment) field campaign (February–March 1999). This area is shown to be a significant portion of the “high‐ozone tropics”. East‐west O3 features and their flow are identified, and ozone origins are compared to other tropical regions, using water vapor as a second tracer. In the study period, multiple processes contribute to O3 column enhancements, their importance varying strongly by latitude: (1) Low‐altitude O3 pollution over the northern Indian Ocean mainly originates from the Indian subcontinent and is traceable to high emission areas. Convective activity south of Sri Lanka helps direct ozone outflow from the northern Indian subcontinent. (2) Middle tropospheric O3 maxima over the northern Indian Ocean originate from various sources, often transitioning within a few hours. Convective venting of Asian pollutants can add 20–30 ppbv to the middle troposphere at 5°N–10°N, alternating with stratospheric influence. (3) A number of cases suggest that strong mixing‐in of stratospheric air along the subtropical jet raised tropospheric O3 in early March by ∼40–50 ppbv, especially poleward of ∼10°N. (4) Influences of lightning and large‐scale biomass burning were not strong during this period, in contrast to the situation in Africa and the South Atlantic or locally in Southeast Asia. This work illustrates successes and limitations in approaches to synthesizing disparate information on trace‐gas distributions taken from satellite retrieval products and ozonesondes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".