Tropical tropospheric ozone morphology and seasonality seen in satellite and in situ measurements and model calculations
Bibliographic record
Abstract
An important issue in satellite remote sensing techniques for retrieving tropical tropospheric ozone is understanding the cause of the disagreement between ozone derived from satellite residual‐based methods and the precursor distributions seen in both the fire count distribution and the Measurements Of Pollution In The Troposphere (MOPITT) CO distribution over northern tropical Atlantic and Africa in boreal winter and spring. This discrepancy has been called the Northern Atlantic paradox; however, it actually extends eastward all the way to Indonesia. We define the disagreement as the northern tropical paradox. We employ the scan angle method (SAM) to solve the paradox. This algorithm takes advantage of the difference in the Total Ozone Mapping Spectrometer (TOMS) retrieval information between nadir and high viewing angles. The averaging kernel for this difference exhibits a broad maximum centered at ∼5 km in the troposphere and thereby can be used to estimate tropospheric ozone information. The seasonal distribution of tropospheric ozone derived from the SAM algorithm shows remarkably good agreement with fire counts from Along Track Scanning Radiometer (ATSR), CO from MOPITT, TOMS aerosol index, and ozone distribution from the GEOS‐CHEM model in four seasons over the tropics. In meridional distribution, all of these products clearly reveal the seasonal oscillation between northern tropical Africa in boreal winter and over southern tropical Africa in boreal summer. The residual‐based methods (TOR, CCD, CCP, and modified residual), however, always show the ozone maximum over the southern Atlantic off the coast of southwest Africa. A further comparison with the in situ measurements from the Measurement of Ozone and Water Vapor by Airbus In‐Service Aircraft (MOZAIC) campaign at three locations over the northern tropics, Abidjan (5°N, 4°W), Madras (13°N, 80°E), and Bangkok (14°N, 101°E), supports our results. The seasonality of ozone from the SAM and the model, which shows the ozone maximum in boreal summer and the minimum in boreal winter, is in accordance with the MOZAIC measurements. However, the seasonality of the RBMs does not agree with the seasonality of in situ measurements. We conclude that the northern tropical paradox does not actually exist.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".