MétaCan
Menu
Back to cohort
Record W2343182715 · doi:10.5194/acp-17-1791-2017

Two mechanisms of stratospheric ozone loss in the Northern Hemisphere, studied using data assimilation of Odin/SMR atmospheric observations

2017· article· en· W2343182715 on OpenAlexfundno aff
Kazutoshi Sagi, Kristell Pérot, D. Murtagh, Yvan Orsolini

Bibliographic record

VenueAtmospheric chemistry and physics · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
FundersCanadian Space AgencyCentre National d’Etudes SpatialesEuropean Space AgencyNorges ForskningsrådTekesUniversity of Leeds
KeywordsStratosphereOzone depletionAtmospheric sciencesEnvironmental scienceOzone layerOzoneClimatologyNorthern HemisphereArcticPolar vortexData assimilationMeteorologyGeologyOceanographyPhysics

Abstract

fetched live from OpenAlex

Abstract. Observations from the Odin/Sub-Millimetre Radiometer (SMR) instrument have been assimilated into the DIAMOND model (Dynamic Isentropic Assimilation Model for OdiN Data), in order to estimate the chemical ozone (O3) loss in the stratosphere. This data assimilation technique is described in Sagi and Murtagh (2016), in which it was used to study the inter-annual variability in ozone depletion during the entire Odin operational time and in both hemispheres. Our study focuses on the Arctic region, where two O3 destruction mechanisms play an important role, involving halogen and nitrogen chemical families (i.e. NOx = NO and NO2), respectively. The temporal evolution and geographical distribution of O3 loss in the low and middle stratosphere have been investigated between 2002 and 2013. For the first time, this has been done based on the study of a series of winter–spring seasons over more than a decade, spanning very different dynamical conditions. The chemical mechanisms involved in O3 depletion are very sensitive to thermal conditions and dynamical activity, which are extremely variable in the Arctic stratosphere. We have focused our analysis on particularly cold and warm winters, in order to study the influence this has on ozone loss. The winter 2010/11 is considered as an example for cold conditions. This case, which has been the subject of many studies, was characterised by a very stable vortex associated with particularly low temperatures, which led to an important halogen-induced O3 loss occurring inside the vortex in the lower stratosphere. We found a loss of 2.1 ppmv at an altitude of 450 K in the end of March 2011, which corresponds to the largest ozone depletion in the Northern Hemisphere observed during the last decade. This result is consistent with other studies. A similar situation was observed during the winters 2004/05 and 2007/08, although the amplitude of the O3 destruction was lower. To study the opposite situation, corresponding to a warm and unstable winter in the stratosphere, we performed a composite calculation of four selected cases, 2003/04, 2005/06, 2008/09 and 2012/13, which were all affected by a major mid-winter sudden stratospheric warming event, related to particularly high dynamical activity. We have shown that such conditions were associated with low O3 loss below 500 K (approximately 20 km), while O3 depletion in the middle stratosphere, where the role of NOx-induced destruction processes prevails, was particularly important. This can mainly be explained by the horizontal mixing of NOx-rich air from lower latitudes with vortex air that takes place in case of strongly disturbed dynamical situation. In this manuscript, we show that the relative contribution of O3 depletion mechanisms occurring in the lower or in the middle stratosphere is significantly influenced by dynamical and thermal conditions. We provide confirmation that the O3 loss driven by nitrogen oxides and triggered by stratospheric warmings can outweigh the effects of halogens in the case of a dynamically unstable Arctic winter. This is the first time that such a study has been performed over a long period of time, covering more than 10 years of observations.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.054
GPT teacher head0.272
Teacher spread0.218 · 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 designSimulation or modeling
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

Citations14
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueAtmospheric chemistry and physicsSame topicAtmospheric Ozone and ClimateFrench-language works237,207