Reconstruction of three‐dimensional ozone fields using POAM III during SOLVE
Bibliographic record
Abstract
In this paper we demonstrate the utility of the Polar Ozone and Aerosol Measurement (POAM) III data for providing semiglobal three‐dimensional ozone fields during the Stratospheric Aerosol and Gas Experiment (SAGE) III Ozone Loss and Validation Experiment (SOLVE) winter. As a solar occultation instrument, POAM III measurements were limited to latitudes of 63°N to 68°N during the SOLVE campaign but covered a wide range of potential vorticity. Using established mapping techniques, we have used the relation between potential vorticity and ozone measured by POAM III to calculate three‐dimensional ozone mixing ratio fields throughout the Northern Hemisphere on a daily basis during the 1999/2000 winter. To validate the results, we have extensively compared profiles obtained from ozonesondes and the Halogen Occultation Experiment to the proxy O3 interpolated horizontally and vertically to the correlative measurement locations. On average, the proxy O3 agrees with the correlative observations to better than ∼5%, at potential temperatures below about 900 K and latitudes above about 30°N, demonstrating the reliability of the reconstructed O3 fields in these regions. We discuss the application of the POAM proxy ozone profiles for calculating photolysis rates along the ER‐2 and DC‐8 flight tracks during the SOLVE campaign, and we present a qualitative picture of the evolution of polar stratospheric ozone throughout the winter.
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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 | 0.001 | 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".