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Record W2990056085 · doi:10.5194/acp-19-14031-2019

Is the recovery of stratospheric O <sub>3</sub> speeding up in the Southern Hemisphere? An evaluation from the first IASI decadal record (2008–2017)

2019· article· en· W2990056085 on OpenAlexaboutno aff
Catherine Wespes, Daniel Hurtmans, Simon Chabrillat, Gaétane Ronsmans, Cathy Clerbaux, Pierre‐François Coheur

Bibliographic record

VenueAtmospheric chemistry and physics · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
FundersServices Fédéraux des Affaires Scientifiques, Techniques et CulturellesEidgenössische Technische Hochschule ZürichCentre National d’Etudes SpatialesUniversité de LiègeLangley Research CenterEuropean Space AgencyNational Aeronautics and Space Administration
KeywordsStratosphereEnvironmental scienceClimatologyAtmospheric sciencesTroposphereSouthern HemisphereLatitudeOzone layerNorthern HemisphereMiddle latitudesQuasi-biennial oscillationOzone depletionOzoneLa NiñaEl Niño Southern OscillationMeteorologyGeographyGeology

Abstract

fetched live from OpenAlex

In this paper, we present the global fingerprint of recent changes in middle–upper stratosphere (MUSt; <25 hPa) ozone (O 3 ) in comparison with lower stratosphere (LSt; 150–25 hPa) O 3 derived from the first 10 years of the IASI/Metop-A satellite measurements (January 2008–December 2017). The IASI instrument provides vertically resolved O 3 profiles with very high spatial and temporal (twice daily) samplings, allowing O 3 changes to be monitored in these two regions of the stratosphere. By applying multivariate regression models with adapted geophysical proxies on daily mean O 3 time series, we discriminate anthropogenic trends from various modes of natural variability, such as the El Niño–Southern Oscillation (ENSO). The representativeness of the O 3 response to its natural drivers is first examined. One important finding relies on a pronounced contrast between a positive LSt O 3 response to ENSO in the extratropics and a negative one in the tropics, with a delay of 3 months, which supports a stratospheric pathway for the ENSO influence on lower stratospheric and tropospheric O 3 . In terms of trends, we find an unequivocal O 3 recovery from the available period of measurements in winter–spring at middle to high latitudes for the two stratospheric layers sounded by IASI (>∼35 ∘ N–S in the MUSt and >∼45 ∘ S in the LSt) as well as in the total columns at southern latitudes (>∼45 ∘ S) where the increase reaches its maximum. These results confirm the effectiveness of the Montreal Protocol and its amendments and represent the first detection of a significant recovery of O 3 concurrently in the lower, in the middle–upper stratosphere and in the total column from one single satellite dataset. A significant decline in O 3 at northern mid-latitudes in the LSt is also detected, especially in winter–spring of the Northern Hemisphere. Given counteracting trends in the LSt and MUSt at these latitudes, the decline is not categorical in total O 3 . When freezing the regression coefficients determined for each natural driver over the whole IASI period but adjusting a trend, we calculate a significant speeding up in the O 3 response to the decline of O 3 -depleting substances (ODSs) in the total column, in the LSt and, to a lesser extent, in the MUSt, at high southern latitudes over the year. Results also show a small significant acceleration of the O 3 decline at northern mid-latitudes in the LSt and in the total column over the last few years. That, specifically, needs urgent investigation to identify its exact origin and apprehend its impact on climate change. Additional years of IASI measurements would, however, be required to confirm the O 3 change rates observed in the stratospheric layers over the last few years.

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 score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.016
GPT teacher head0.219
Teacher spread0.203 · 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

Citations10
Published2019
Admission routes1
Has abstractyes

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