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Record W2095440455 · doi:10.1175/jas-d-13-0146.1

Entropy Evolution Characteristics Associated with the Development of the South Asian Monsoon

2013· article· en· W2095440455 on OpenAlexaff
Jiangnan Li, Tim Li

Bibliographic record

VenueJournal of the Atmospheric Sciences · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsEntropy productionDissipationMonsoonClimatologyEntropy (arrow of time)Environmental scienceAtmospheric sciencesMeteorologyGeologyPhysicsStatistical physicsThermodynamics

Abstract

fetched live from OpenAlex

Abstract The structure and evolution characteristics of atmospheric entropy production associated with the climatologic monsoon onset and evolution were investigated using the National Centers for Environmental Prediction (NCEP) reanalysis data. The entropy balance equation contains two parts. The first part is internal entropy production that corresponds to natural dissipation. The second part is external entropy production that is associated with lower-boundary entropy supply. It is shown that the dissipation process represented by internal entropy production can be used to describe the thermal and dynamical structures of the monsoon. The thermal dissipation due to turbulent vertical diffusion and convection is highly correlated to precipitation. The dynamic dissipation due to wind stress becomes very strong over the Arabian Sea and southwestern part of India in boreal summer, and dynamic dissipation can describe the monsoon structure more clearly than variables such as wind shear. The correlation between surface entropy supply and internal entropy production is so large that the surface entropy supply can also be used to evaluate the monsoon. Over the desert region of Rajasthan, the dissipation is relatively weaker than its surroundings owing to descending large-scale eddy flow and a weak convective flux. The analysis of atmospheric entropy provides a new way to describe the monsoon development characteristics, which differs from those derived from a traditional analysis method.

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)0.001
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.199
Teacher spread0.187 · 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
Published2013
Admission routes1
Has abstractyes

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