Status of the TEMPO total ozone and ozone profile data products: A comprehensive validation using various satellites and ground-based observations
Bibliographic record
Abstract
The Tropospheric Emissions: Monitoring of Pollution (TEMPO) is part of the global geostationary air quality monitoring constellation. It is the first satellite instrument in geostationary orbit dedicated to monitor air pollutants across North America. Its observational coverage extends from Mexico City to the Canadian oil sands and from the Atlantic Ocean to the Pacific, with hourly measurements at a resolution approaching neighborhood scale. Following its successful launch in April 2023, TEMPO began nominal operations in October 2023. TEMPO L2 data products (NO2, HCHO, Cloud and total ozone) were made publicly available in May 2024, following the release of Level 1 data in February 2024. As of December 2024, these products have been classified as the Provisional maturity level.This presentation highlights the evaluation of the TEMPO total ozone (O3TOT) product and introduces improvements to the TEMPO ozone profile (O3PROF) product. We present a comparative analysis of total ozone columns (TOCs) from TEMPO observations against data from other satellite instruments, such as OMPS, OMI, and TROPOMI, as well as ground-based measurements from Pandora, Brewer, and Dobson instruments. Additionally, we present enhancements to the TEMPO O3PROF algorithm, particularly the empirical correction, which is scheduled for release this year. Furthermore, we compare TEMPO tropospheric ozone columns with those from EPIC, OMI, and TROPOMI satellites. Lastly, the TEMPO O3PROF product is evaluated using ground-based observations, including data from the Tropospheric Ozone Lidar Network (TOLNet) and ozonesonde observations.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".