On shifts in the long‐term Umkehr radiance records and their influence on retrieved ozone profiles
Bibliographic record
Abstract
The Umkehr technique has been used routinely for more than 40 years to assess features in the vertical distribution of ozone. The measurements represent the longest ozone profile data record in existence. A careful examination of the long‐term Umkehr N‐value (radiance) measurement record, archived at the WMO World Ozone and UV Data Center in Toronto, Canada, revealed shifts in the data. These shifts appear to be mainly related to Dobson instrument calibrations and/or to instrument changes at the observing stations. In most cases, the detected shifts exhibit solar zenith angle dependence. The standard procedure of subtracting the Umkehr measurement at 60‐degree solar zenith angle (or the next smallest SZA available) from the measurement at the other angles to eliminate the instrumental and extraterrestrial constants from measurements does not necessarily remove the shifts. The shift errors would appear as shifts in the retrieved ozone profiles and could affect any ozone profile analysis (including ozone trends) as well as comparisons with other profiles derived from satellite and lidar measurements. A preliminary approach for detecting the shifts and allowing for corrections is developed and evaluated for its potential to improve the quality of the of the Umkehr records.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.005 |
| 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".