Indicators of the ozone recovery for selected sites in the Northern Hemisphere mid-latitudes derived from various total column ozone datasets (1980–2020)
Bibliographic record
Abstract
We propose a method to examine the current status of the ozone recovery attributed to changes of ozone-depleting substances (ODS) in the stratosphere. The total column ozone (TCO 3 ) datasets used are based on the ground-based (by the Dobson and/or Brewer spectrophotometer) measurements, satellite observations (from the Solar Backscatter Ultraviolet (SBUV) and Ozone Mapping and Profiler Suite (OMPS) instruments), and output of reanalyses (Multi-Sensor Reanalysis version 2 (MSR2) and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA2)). The TCO 3 time series are calculated for selected sites in the mid-latitudes of the Northern Hemisphere (NH, 35–60 ∘ N), which are station locations with long-term TCO 3 observations archived at the World Ozone and Ultraviolet Radiation Data Centre (WOUDC). The TCO 3 monthly means (1980–2020) are averaged over the April–September period to obtain TCO 3 time series for the warm sub-period of the year. Two types of the averaged TCO 3 time series are considered: the original one and non-proxy time series with removed natural variability by a standard multiple regression model. The TCO 3 time series were smoothed by the locally weighted scatterplot smoother (LOWESS) and the super smoother (SS). The smoothed TCO 3 values in 1980, 1988, 1997, and 2020 were used to build ozone recovery indices (ORIs) in 2020. These are key years in the equivalent effective stratospheric chlorine (EESC) time series for the period 1980–2020, i.e., the stratosphere was only slightly contaminated by ODS in 1980, 1988 is the year in which the EESC value is equal to its value at the end (2020), and in 1997, the EESC maximum was in mid-latitude stratosphere. The first proposed ORI, ORI 1 , is the normalized difference between the TCO 3 values in 2020 and 1988. The second one, ORI 2 , is the percentage of the recovered TCO 3 in 2020 since the ODS maximum. Following these definitions, the corresponding reference ranges (from −0.5 % to 1 % for ORI 1 and from 40 % to 60 % for ORI 2 ) are obtained by analyzing a set of possible EESC time series simulated via the Goddard automailer. The ozone recovery phases are classified comparing the current ORI values and their uncertainty ranges (by the bootstrapping) with these reference ranges. In the analyzed TCO 3 time series, for specific combinations of datasets, data types, and the smoother used, we find faster (for ORI 1 or ORI 2 above the reference range) and slower (for ORI 1 or ORI 2 below the reference range) recovery in 2020 than that inferred from the EESC change, and a continuation of the TCO 3 decline after the EESC peak (ORI 2 <0 %). Strong signal of the slower TCO 3 recovery is found in Toronto, Hohenpeissenberg, Hradec Kralove, and Belsk. A continuation of ozone decline after the turnaround in ODS concentration is found in both the original and non-proxy time series from WOUDC (Toronto), SBUV and OMPS (Toronto, Arosa, Hohenpeissenberg, Uccle, Hradec Kralove, and Belsk), and MERRA2 data (Arosa, Hohenpeissenberg, Hradec Kralove, and Belsk).
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 | 0.001 |
| 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".