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Record W4389992056 · doi:10.5194/acp-23-15655-2023

Trends in polar ozone loss since 1989: potential sign of recovery in the Arctic ozone column

2023· article· en· W4389992056 on OpenAlexaff
Andréa Pazmiño, F. Goutail, Sophie Godin‐Beekmann, Alain Hauchecorne, Jean‐Pierre Pommereau, Martyn P. Chipperfield, Wuhu Feng, Franck Lefèvre, Audrey Lecouffe, Michel Van Roozendaël, Nis Jepsen, Georg Hansen, Rigel Kivi, Kimberly Strong, Kaley A. Walker

Bibliographic record

VenueAtmospheric chemistry and physics · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsUniversity of Toronto
FundersNatural Environment Research CouncilCentre National de la Recherche ScientifiqueSight Research UK
KeywordsOzonePolar vortexOzone depletionAtmospheric sciencesOzone layerNorthern HemisphereEnvironmental sciencePolarClimatologyStratosphereMeteorologyGeologyPhysics

Abstract

fetched live from OpenAlex

Abstract. Ozone depletion over the polar regions is monitored each year by satellite- and ground-based instruments. In this study, the vortex-averaged ozone loss over the last 3 decades is evaluated for both polar regions using the passive ozone tracer of the chemical transport model TOMCAT/SLIMCAT and total ozone observations from Système d'Analyse par Observation Zénithale (SAOZ) ground-based instruments and Multi-Sensor Reanalysis (MSR2). The passive-tracer method allows us to determine the evolution of the daily rate of column ozone destruction and the magnitude of the cumulative column loss at the end of the winter. Three metrics are used in trend analyses that aim to assess the ozone recovery rate over both polar regions: (1) the maximum ozone loss at the end of the winter, (2) the onset day of ozone loss at a specific threshold, and (3) the ozone loss residuals computed from the differences between annual ozone loss and ozone loss values regressed with respect to sunlit volume of polar stratospheric clouds (VPSCs). This latter metric is based on linear and parabolic regressions for ozone loss in the Northern Hemisphere and Southern Hemisphere, respectively. In the Antarctic, metrics 1 and 3 yield trends of −2.3 % and −2.2 % per decade for the 2000–2021 period, significant at 1 and 2 standard deviations (σ), respectively. For metric 2, various thresholds were considered at the total ozone loss values of 20 %, 25 %, 30 %, 35 %, and 40 %, all of them showing a time delay as a function of year in terms of when the threshold is reached. The trends are significant at the 2σ level and vary from 3.5 to 4.2 d per decade between the various thresholds. In the Arctic, metric 1 exhibits large interannual variability, and no significant trend is detected; this result is highly influenced by the record ozone losses in 2011 and 2020. Metric 2 is not applied in the Northern Hemisphere due to the difficulty in finding a threshold value in enough of the winters. Metric 3 provides a negative trend in Arctic ozone loss residuals with respect to the sunlit VPSC fit of −2.00 ± 0.97 (1σ) % per decade, with limited significance at the 2σ level. With such a metric, a potential quantitative detection of ozone recovery in the Arctic springtime lower stratosphere can be made.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.008
GPT teacher head0.206
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2023
Admission routes1
Has abstractyes

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