Total ozone trends and variability during 1979–2012 from merged datasets of various satellites
Notice bibliographique
Résumé
Abstract. The study presents a~long term statistical trend analysis of total ozone datasets obtained from various satellites. A multi-variate linear regression was applied to annual mean zonal mean data using various natural and anthropogenic explanatory variables that represent dynamical and chemical processes which modify global ozone distributions in a changing climate. The study investigated the magnitude and zonal distribution of the different atmospheric chemical and dynamical factors to long-term total ozone changes. The regression model included the equivalent effective stratospheric chlorine (EESC), the 11 yr solar cycle, the Quasi-Biennial Oscillation (QBO), stratospheric aerosol loading describing the effects from major volcanic eruptions, the El Niño/Southern Oscillation (ENSO), the Arctic and Antarctic Oscillation (AO/AAO), and accumulated eddy heat flux (EHF), the latter representing changes due to the Brewer–Dobson circulation. The total ozone column dataset used here comprises the SBUV/TOMS/OMI merged data (1979–2012) MOD V8.0, the SBUV/SBUV-2 merged V8.6 and the merged GOME/SCIAMACHY/GOME-2 (GSG) WFDOAS merged data (1995–2012). The trend analysis was performed for twenty six 5° wide latitude bands from 65° S to 65° N, the analysis explained most of the ozone variability. The results show that QBO dominates the ozone variability in the tropics (±7 DU) while at higher latitudes, the dynamical indices, AO/AAO and eddy heat flux, have substantial influence on total ozone variations by up to ±10 DU. Volcanic aerosols are only prominent during the eruption periods and these together with the ENSO signal are more evident in the Northern Hemisphere. The signature of the solar cycle is evident over all latitudes and contributes about 10 DU from solar maximum to solar minimum. EESC is found to be a main contributor to the long-term ozone decline and the trend changes after the end of 1990s. A positive significant trend in total ozone columns is found after 1997 (between 1 and 8.2 DU decade−1) which points at the slowing of ozone decline and the onset of ozone recovery. The EESC based trends are compared with the trends obtained from the statistical piecewise linear trend (PWLT or hockey stick) model with a turnaround in 1997 to examine the differences between both approaches. Similar and significant pre-turnaround trends are observed. On the other hand, our results do indicate that the positive PWLT turnaround trends are larger than indicated by the EESC trends, however, they agree within 2-sigma, thus demonstrating the success of the Montreal Protocol phasing out of the ozone depleting substances (ODS). A sensitivity study is carried out by comparing the regression results, using SBUV MOD 8.0 merged time series (1979–2012) and a merged dataset combining TOMS/SBUV (1979–June 1995) and GOME/SCIAMACHY/GOME-2 ("GSG") WFDOAS (Weighting Function DOAS) (July 1995–2012) as well as SBUV/SBUV-2 MOD 8.6 (1979–2012) in the regression analysis in order to investigate the uncertainty in the long-term trends due to different ozone datasets and data versions. Replacing the late SBUV merged data record with GSG data (unscaled and adjusted) leads to very similar results demonstrating the high consistency between satellite datasets. However, the comparison of the new SBUV merged Mod V8.6 with the V8.0 data showed somewhat smaller sensitivities with regard to several proxies, however, the EESC and PWLT trends are very similar. On the other hand, the new MOD 8.6 data in the PWLT model revealed a~reduced ODS related upward trend after 1997.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».