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Record W4292707968 · doi:10.5194/acp-22-10657-2022

Atmospheric impacts of chlorinated very short-lived substances over the recent past – Part 1: Stratospheric chlorine budget and the role of transport

2022· article· en· W4292707968 on OpenAlexaboutno aff
Ewa Bednarz, Ryan Hossaini, Martyn P. Chipperfield, Nathan Luke Abraham, Peter Braesicke

Bibliographic record

VenueAtmospheric chemistry and physics · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
FundersNatural Environment Research CouncilSight Research UK
KeywordsStratosphereChemistryAtmospheric sciencesChlorineMeteorologyAtmospheric chemistryClimatologyAtmosphere (unit)InterimEnvironmental scienceOzonePhysics

Abstract

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Abstract. Impacts of chlorinated very short-lived substances (Cl-VSLS) on stratospheric chlorine budget over the first two decades of the 21st century are assessed using the Met Office’s Unified Model coupled to the United Kingdom Chemistry and Aerosol (UM-UKCA) chemistry–climate model; this constitutes the most up-to-date assessment and the first study to simulate Cl-VSLS impacts using a whole atmosphere chemistry–climate model. We examine the Cl-VSLS responses using a small ensemble of free-running simulations and two pairs of integrations where the meteorology was “nudged” to either ERA5 or ERA-Interim reanalysis. The stratospheric chlorine source gas injection due to Cl-VSLS estimated from the free-running integrations doubled from ∼40 ppt Cl injected into the stratosphere in 2000 to ∼80 ppt Cl injected in 2019. Combined with chlorine product gas injection, the integrations showed a total of ∼130 ppt Cl injected into the stratosphere in 2019 due to Cl-VSLS. The use of the nudged model significantly increased the abundance of Cl-VSLS simulated in the lower stratosphere relative to the free-running model. Averaged over 2010–2018, simulations nudged to ERAI-Interim and ERA5 showed 20 ppt (i.e. a factor of 2) and 10 ppt (i.e. ∼50 %) more Cl, respectively, in the tropical lower stratosphere at 20 km in the form of Cl-VSLS source gases compared to the free-running case. These differences can be explained by the corresponding differences in the speed of the large-scale circulation. The results illustrate the strong dependence of the simulated stratospheric Cl-VSLS levels on the model dynamical fields. In UM-UKCA, this corresponds to the choice between free-running versus nudged set-up, and to the reanalysis dataset used for nudging. Temporal changes in Cl-VSLS are found to have significantly impacted recent HCl and COCl2 trends in the model. In the tropical lower stratosphere, the inclusion of Cl-VSLS reduced the magnitude of the negative HCl and COCl2 trends (e.g. from ∼-8%(HCl)/decade and ∼-4 ppt(COCl2)/decade at ∼20 km to ∼-6%(HCl)/decade and ∼ −2 ppt(COCl2)/decade in the free running simulations) and gave rise to positive tropospheric trends in both tracers. In the tropics, both the free-running and nudged integrations with Cl-VSLS included compared much better to the observed trends from the ACE-FTS satellite record than the analogous simulations without Cl-VSLS. Since observed HCl trends provide information on the evolution of total stratospheric chlorine and, thus, the effectiveness of the Montreal Protocol, our results demonstrate that Cl-VSLS are a confounding factor in the interpretation of such data and should be factored into future analysis. Unlike the nudged model runs, the ensemble mean free-running integrations did not reproduce the hemispheric asymmetry in the observed mid-latitude HCl and COCl2 trends related to short-term dynamical variability. The individual ensemble members also showed a considerable spread of the diagnosed tracer trends, illustrating the role of natural interannual variability in modulating the diagnosed responses and the need for caution when interpreting both model and observed tracer trends derived over a relatively short time period.

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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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.250
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.007
GPT teacher head0.193
Teacher spread0.186 · 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

Citations21
Published2022
Admission routes1
Has abstractyes

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