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Record W1841972637 · doi:10.1002/2015ea000115

An examination of convective moistening of the lower stratosphere using satellite data

2015· article· en· W1841972637 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEarth and Space Science · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologies
KeywordsStratosphereTropopauseMicrowave Limb SounderConvectionSatelliteWater vaporAtmospheric sciencesEnvironmental scienceDeep convectionClimatologyGeologyMeteorologyGeographyPhysics

Abstract

fetched live from OpenAlex

Abstract In this paper, we use satellite data to test the hypothesis that deep convection moistens the lower stratosphere. Water vapor measurements from Earth Observing System‐Microwave Limb Sounder and Atmospheric Chemistry Experiment‐Fourier Transform Spectrometer over North America are binned according to the International Satellite Cloud Climatology Project deep convection indices. The results show that in the North American region (50–112°W, 10–50°N) the convection‐impacted samples are significantly moister than the nonimpact samples in the lowermost stratospheric layer right above the tropopause, and a drier tendency is also noticed right above this moistened layer. Trajectory modeling is used to aid the identification of deep convection‐impacted water vapor samples. However, we find that a substantial fraction of high‐concentration (>8 ppmv) samples at 100 hPa cannot be attributed to nearby deep convections.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.226

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.042
GPT teacher head0.259
Teacher spread0.216 · 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