Ozone trends in homogenized Umkehr, ozonesonde, and COH overpass records
Bibliographic record
Abstract
This study presents an updated evaluation of stratospheric ozone profile trends at Arosa/Davos/Hohenpeißenberg, Switzerland/Germany; Observatory de Haute-Provence (OHP), France; Boulder, Colorado, Mauna Loa Observatory (MLO) and Hilo, Hawaii; and Lauder, Aotearoa / New Zealand, with a focus on the ozone recovery period post-2000. Trends are derived using vertical ozone profiles from NOAA's Dobson network via the Umkehr method (with a recent new homogenization), ozonesondes, and the NOAA COHesive Solar Backscatter Ultraviolet Instrument (SBUV)/Ozone Mapping and Profiler Suite (OMPS) satellite-based record (COH) sampled to match the geographical coordinates of the ground-based stations used in this study. Analyses of long-term changes in stratospheric ozone time series were performed using the updated version (0.8.0) of the Long-term Ozone Trends and Uncertainties in the Stratosphere (LOTUS) independent linear trend (ILT) regression model. This study finds consistency between the trends derived from the different observational records, which is a key factor to the understanding of the recovery of the ozone layer after the implementation of the Montreal Protocol and its amendments that control ozone-depleting substance production and release into the atmosphere. The northern hemispheric Umkehr records of Arosa/Davos, OHP, and MLO all show positive trends in the mid- to upper stratosphere, with trends peaking at ∼ +2 % per decade. Although the upper-stratospheric ozone trends derived from COH satellite records are more positive than those detected by the Umkehr system, the agreement is within the 2 times the standard error uncertainty. Umkehr trends in the upper stratosphere at Boulder and Lauder are positive but not statistically significant, while COH trends are larger and statistically significant (within 2 times the standard error uncertainty). In the lower stratosphere, trends derived from Umkehr and ozonesonde records are mostly negative (except for positive ozonesonde trends at OHP); however, the uncertainties are quite large. Additional dynamical proxies were investigated in the LOTUS model at five ground-based sites. The use of additional proxies did not significantly change trends, but the equivalent latitude reduced the uncertainty in the Umkehr and COH trends in the upper stratosphere and at higher latitudes. In lower layers, additional predictors (tropopause pressure for all stations; two extra components of Quasi-Biennial Oscillation at MLO; Arctic Oscillation at Arosa/Davos, OHP, and MLO) improve the model fit and reduce trend uncertainties as seen by Umkehr and sonde.
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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) | 0.000 | 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".