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Record W2155647793 · doi:10.1175/2010jcli3404.1

Chemistry–Climate Model Simulations of Twenty-First Century Stratospheric Climate and Circulation Changes

2010· article· en· W2155647793 on OpenAlexafffund
Neal Butchart, Irene Cionni, Veronika Eyring, Theodore G. Shepherd, Darryn W. Waugh, Hideharu Akiyoshi, J. Austin, C. Brühl, Martyn P. Chipperfield, Eugene C. Cordero, M. Dameris, R. Deckert, Sandip Dhomse, S. M. Frith, Rolando R. García, Andrew Gettelman, M. A. Giorgetta, Douglas E. Kinnison, Feng Li, E. Mancini, C. McLandress, Steven Pawson, Giovanni Pitari, David A. Plummer, Eugene Rozanov, Fabrizio Sassi, John Scinocca, Kiyotaka Shibata, B. Steil, Wenshou Tian

Bibliographic record

VenueJournal of Climate · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsUniversity of VictoriaEnvironment and Climate Change CanadaUniversity of Toronto
FundersNatural Environment Research CouncilAmes Research CenterScheme for Promotion of Academic and Research CollaborationNational Institute for Environmental StudiesNational Aeronautics and Space AdministrationDepartment for Environment, Food and Rural Affairs, UK GovernmentMinistry of Education, IndiaEuropean CommissionSight Research UKCanadian Foundation for Climate and Atmospheric Sciences
KeywordsStratosphereClimatologyAtmospheric sciencesOzone depletionEnvironmental scienceDownwellingOzone layerClimate modelNorthern HemisphereArcticPolar vortexClimate changeGreenhouse gasPolar nightOceanographyGeologyUpwelling

Abstract

fetched live from OpenAlex

Abstract The response of stratospheric climate and circulation to increasing amounts of greenhouse gases (GHGs) and ozone recovery in the twenty-first century is analyzed in simulations of 11 chemistry–climate models using near-identical forcings and experimental setup. In addition to an overall global cooling of the stratosphere in the simulations (0.59 ± 0.07 K decade−1 at 10 hPa), ozone recovery causes a warming of the Southern Hemisphere polar lower stratosphere in summer with enhanced cooling above. The rate of warming correlates with the rate of ozone recovery projected by the models and, on average, changes from 0.8 to 0.48 K decade−1 at 100 hPa as the rate of recovery declines from the first to the second half of the century. In the winter northern polar lower stratosphere the increased radiative cooling from the growing abundance of GHGs is, in most models, balanced by adiabatic warming from stronger polar downwelling. In the Antarctic lower stratosphere the models simulate an increase in low temperature extremes required for polar stratospheric cloud (PSC) formation, but the positive trend is decreasing over the twenty-first century in all models. In the Arctic, none of the models simulates a statistically significant increase in Arctic PSCs throughout the twenty-first century. The subtropical jets accelerate in response to climate change and the ozone recovery produces a westward acceleration of the lower-stratospheric wind over the Antarctic during summer, though this response is sensitive to the rate of recovery projected by the models. There is a strengthening of the Brewer–Dobson circulation throughout the depth of the stratosphere, which reduces the mean age of air nearly everywhere at a rate of about 0.05 yr decade−1 in those models with this diagnostic. On average, the annual mean tropical upwelling in the lower stratosphere (∼70 hPa) increases by almost 2% decade−1, with 59% of this trend forced by the parameterized orographic gravity wave drag in the models. This is a consequence of the eastward acceleration of the subtropical jets, which increases the upward flux of (parameterized) momentum reaching the lower stratosphere in these latitudes.

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)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
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 head0.011
GPT teacher head0.228
Teacher spread0.217 · 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

Citations340
Published2010
Admission routes2
Has abstractyes

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