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Record W2007767825 · doi:10.5539/esr.v1n1p87

Role of Tropical Convective Cells in the Observed Middle Atmospheric Gravity Wave Properties from Two Distant Low Latitude Stations

2012· article· en· W2007767825 on OpenAlexvenueno aff
Alok Taori, S. Raizada, M. Venkat Ratnam, C. A. Tepley, Debashis Nath, A. Jayaraman

Bibliographic record

VenueEarth Science Research · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsnot available
FundersUniversities Space Research AssociationNational Science Foundation
KeywordsGravity waveConvectionAtmospheric sciencesLatitudeLow latitudeAtmospheric dynamicsGeophysicsAtmosphere (unit)Environmental scienceGeologyClimatologyPhysicsMeteorologyGravitational waveAstrophysicsGeodesy

Abstract

fetched live from OpenAlex

We investigate the role of convective processes in triggering middle atmospheric gravity waves with the help of simultaneous measurements of middle atmospheric temperature variability from two tropical stations, Gadanki (13.5oN, 79.2oE) and Arecibo (18.3oN, 66.7oW). Our data reveal that some of the wave periods are similar at both locations indicating the source regions of waves to be similar at both the stations. However, the potential energies of short period gravity waves are found to be significantly higher over Gadanki compared to that at Arecibo. The most striking observation is that background wind conditions were similar and convective processes occurred very close to Gadanki compared to Arecibo. In the view absence of other wave sources during the period of observations, we suggest the strength as well as the distance of convective cells from the location of the observations is responsible for the observed differences in gravity wave spectrum and energies.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.021

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 communication0.0010.000
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 head0.058
GPT teacher head0.295
Teacher spread0.237 · 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 designObservational
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
Published2012
Admission routes1
Has abstractyes

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