MétaCan
Menu
Back to cohort
Record W1972793351 · doi:10.1006/asle.2001.0027

Global warming potentials modified for surface radiative forcing for use in surface energy balance models

2001· article· en· W1972793351 on OpenAlexafffund
W. F. J. Evans, E. Puckrin

Bibliographic record

VenueAtmospheric Science Letters · 2001
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsTrent University
FundersAir Force Research LaboratoryNatural Sciences and Engineering Research Council of Canada
KeywordsRadiative forcingGreenhouse gasEnvironmental scienceAtmospheric sciencesForcing (mathematics)ClimatologyEarth's energy budgetGlobal warmingRadiative transferEnergy balanceTropopauseClimate modelWater vaporCloud forcingGreenhouse effectClimate changeWater balanceTroposphereMeteorologyRadiationPhysicsAerosolThermodynamicsGeology

Abstract

fetched live from OpenAlex

Abstract The radiative impact of greenhouse gases in warming the Earth varies significantly, depending on whether one considers the forcing at the tropopause or at the surface. Compared to the former, the surface forcing for some greenhouse gases is reduced by the interference of water vapour. Hence, we calculate alternative surface global warming potentials (SGWPs) that are derived from the surface forcing radiation of greenhouse gases for potential use in surface radiative energy balance models (SREBMs). For gases with a large water vapour overlap, the SGWPs are typically 30% smaller than current GWPs; for gases with relatively little overlap, the SGWPs are larger by more than 33%. These results may be used in conjunction with SREBMs as an additional means of calculating climate change, and may lead to an altered emissions budget compared to that outlined by the current Kyoto agreement. Copyright © 2003 Royal Meteorological Society.

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: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.025
GPT teacher head0.239
Teacher spread0.214 · 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

Citations10
Published2001
Admission routes2
Has abstractyes

Explore more

Same venueAtmospheric Science LettersSame topicAtmospheric Ozone and ClimateFrench-language works237,207