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Record W2894152094 · doi:10.1029/2018gl078903

Evidence for Radiative‐Convective Bistability in Tropical Atmospheres

2018· article· en· W2894152094 on OpenAlexafffund
Maura Dewey, Colin Goldblatt

Bibliographic record

VenueGeophysical Research Letters · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversity of Victoria
FundersCanadian Space Agency
KeywordsConvectionAtmospheric sciencesOutgoing longwave radiationLongwaveEnvironmental scienceAtmosphere (unit)Radiative transferRadiant energyGreenhouse effectRadiative coolingTroposphereClimate modelClimatologyPhysicsClimate changeMeteorologyGlobal warmingRadiationGeology

Abstract

fetched live from OpenAlex

Abstract Earth's energy balance requires that energy absorbed and emitted at the top of the atmosphere be equal; to first order this balance is maintained via the Planck feedback: outgoing longwave radiation increases as surface temperature increases. Failure of the Planck feedback to stabilize the climate is described by three generally independent phenomena: the super‐greenhouse effect, the runaway greenhouse, and multiple equilibria of radiative‐convective atmospheres. Here we use satellite observations and models to show that the existence of the super‐greenhouse gives rise to a radiative‐convective instability which is relevant to Earth's tropics. The super‐greenhouse is caused by the low troposphere becoming optically thick, causing a positive feedback on near surface temperature and moisture, driving deep convection, column moistening, and reduced outgoing longwave radiation. Aspects of the runaway greenhouse physics are implicated, but a local runaway greenhouse is avoided. These results have implications for understanding the response of the tropics to a warming world.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.126
GPT teacher head0.385
Teacher spread0.259 · 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

Citations7
Published2018
Admission routes2
Has abstractyes

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