MétaCan
Menu
← Back to cohort
Record W4242968020 · doi:10.5194/acpd-5-7309-2005

Convective damping of buoyancy anomalies and its effect on lapse rates in the tropical lower troposphere

2005· preprint· en· W4242968020 on OpenAlexafffund
I. Folkins

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Foundation for Climate and Atmospheric Sciences
KeywordsTroposphereConvectionAtmospheric sciencesBuoyancyLapse rateClimatologyRadiative transferGeologyEnvironmental sciencePhysicsMeteorologyMechanics

Abstract

fetched live from OpenAlex

Abstract. In actively convecting regions of the tropics, lapse rates in the lower troposphere (2.0 km to 5.2 km) vary with height in a way which is inconsistent with both reversible moist adiabatic and pseudoadiabatic assumptions. It is argued that this anomalous behavior arises from the tendency for the divergence of a convective buoyancy anomaly to be primarily offset by the collective divergence of all other updrafts and downdrafts within one Rossby radius of deformation. (Ordinarily, convective divergences are at least partially offset by an induced radiative divergence in the background atmosphere.) If convective divergences are balanced purely by other convective divergences, it would force the vertical clear sky radiative mass flux to be independent of altitude. This is consistent with what is observed at several radiosonde locations in the Western Tropical Pacific between 2.0 and 5.2 km. It is conjectured, that at tropical locations where SST's exceed 27°C over a region whose horizontal extent exceeds the local Rossby radius, this condition on the clear sky radiative mass flux serves to partially constrain the range of physically allowed mean temperature and moisture profiles in the lower troposphere.

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 score0.004
Threshold uncertainty score0.008

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 head0.015
GPT teacher head0.264
Teacher spread0.249 · 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

Citations1
Published2005
Admission routes2
Has abstractyes

Explore more

Same topicClimate variability and models→French-language works237,207→