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Record W2322568457 · doi:10.5194/acp-16-10725-2016

20 years of ClO measurements in the Antarctic lower stratosphere

2016· article· en· W2322568457 on OpenAlexaboutno aff
Gerald E. Nedoluha, B. J. Connor, T. Mooney, James W. Barrett, A. Parrish, R. Michael Gomez, Ian Boyd, Douglas Allen, Michael Kotkamp, Stefanie Kremser, Terry Deshler, Paul A. Newman, M. L. Santee

Bibliographic record

VenueAtmospheric chemistry and physics · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
FundersU.S. Naval Research LaboratoryOffice of Naval ResearchNational Aeronautics and Space AdministrationCalifornia Institute of TechnologyJet Propulsion LaboratoryAntarctica New ZealandNational Science Foundation
KeywordsMicrowave Limb SounderStratosphereAtmospheric sciencesChemistryClimatologyPolar vortexEnvironmental scienceGeology

Abstract

fetched live from OpenAlex

Abstract. We present 20 years (1996–2015) of austral springtime measurements of chlorine monoxide (ClO) over Antarctica from the Chlorine Oxide Experiment (ChlOE1) ground-based millimeter wave spectrometer at Scott Base, Antarctica, as well 12 years (2004–2015) of ClO measurements from the Aura Microwave Limb Sounder (MLS). From August onwards we observe a strong increase in lower stratospheric ClO, with a peak column amount usually occurring in early September. From mid-September onwards we observe a strong decrease in ClO. In order to study interannual differences, we focus on a 3-week period from 28 August to 17 September for each year and compare the average column ClO anomalies. These column ClO anomalies are shown to be highly correlated with the average ozone mass deficit for September and October of each year. We also show that anomalies in column ClO are strongly anti-correlated with 30 hPa temperature anomalies, both on a daily and an interannual timescale. Making use of this anti-correlation we calculate the linear dependence of the interannual variations in column ClO on interannual variations in temperature. By making use of this relationship, we can better estimate the underlying trend in the total chlorine (Cly = HCl + ClONO2 + HOCl + 2 × Cl2 + 2 × Cl2O2 + ClO + Cl). The resultant trends in Cly, which determine the long-term trend in ClO, are estimated to be −0.5 ± 0.2, −1.4 ± 0.9, and −0.6 ± 0.4 % year−1, for zonal MLS, Scott Base MLS (both 2004–2015), and ChlOE (1996–2015) respectively. These trends are within 1σ of trends in stratospheric Cly previously found at other latitudes. The decrease in ClO is consistent with the trend expected from regulations enacted under the Montreal Protocol.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.207
Teacher spread0.193 · 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 teacher head, not a consensus.

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

Citations16
Published2016
Admission routes1
Has abstractyes

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