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Comment on egusphere-2024-2117

2024· peer-review· en· W4402546234 on OpenAlexaff

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsEnvironment and Climate Change CanadaUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsArt

Abstract

fetched live from OpenAlex

Abstract. Climate models predict that the Brewer-Dobson Circulation (BDC) will accelerate due to tropospheric warming. This would increase trace gas transport from the tropics to higher latitudes and alter the spatial distribution of greenhouse gases and therefore impact the radiative properties of the atmosphere, resulting in a feedback effect. The stratospheric “age of air”, representing the time since air in the stratosphere exited the troposphere, serves as a diagnostic tool for assessing stratospheric transport. Changes in age of air can therefore indicate changes in the BDC, but detecting these changes requires a long-term observation-based record of age of air. The long-lived trace gas sulfur hexafluoride (SF6) has an increasing concentration in the troposphere and can serve as a clock to derive age of air. However, it is difficult to measure due to its small concentrations, so historically, the availability of age of air datasets derived from SF6 has been limited. Existing datasets include age of air derived from balloon- and aircraft-based measurements from the 1970s to the present and using satellite-based measurements from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) for the 2002–2012 period. The Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) provides the longest available continuous time series of vertically-resolved SF6 measurements, spanning 2004 to the present. In this study, a new age of air product is derived from the ACE-FTS SF6 dataset. The method is also applied to the MIPAS SF6 dataset. The ACE-FTS product is in good agreement with other observation-based age of air datasets and shows the expected global distribution of age of air values. Two applications of the dataset are then demonstrated: evaluating age of air in a chemistry climate model and calculating the linear trend in age of air in twelve regions within the lower stratospheric midlatitudes (14–20 km, 40–70°) in each hemisphere. All trends are negative and significant to two standard deviations. This is therefore the first observation-based age of air trend study to suggest an acceleration of the shallow branch of the BDC, which transports air poleward in the lower stratosphere, in both hemispheres.

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)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.350
Threshold uncertainty score0.928

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0230.012
Insufficient payload (model declined to judge)0.3500.259

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 head0.052
GPT teacher head0.272
Teacher spread0.221 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2024
Admission routes1
Has abstractyes

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