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Record W2408159063 · doi:10.5539/esr.v5n2p90

Initiation and Maintenance Mechanisms for Heavy Precipitation System over a Mountainous Island under a Prevailing Monsoon Current

2016· article· en· W2408159063 on OpenAlexvenueno aff
Yuh‐Lang Lin, K.-Y. Lee, C.-S. Chen, Fang Cheng, Pay‐Liam Lin, Jen-Hsin Teng, C.-L. Liu

Bibliographic record

VenueEarth Science Research · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMeteorological Phenomena and Simulations
Canadian institutionsnot available
FundersNational Science CouncilNational Central UniversityNational Science Foundation
KeywordsClimatologyPrecipitationOutflowMesoscale meteorologyStormMonsoonMesoscale convective systemConvective available potential energyGeologyCurrent (fluid)InflowFroude numberFlow (mathematics)Environmental scienceMeteorologyGeographyOceanography

Abstract

fetched live from OpenAlex

In this study, the initiation and maintenance mechanisms of two long-lived, summer heavy rainfall systems over Taiwan are investigated by performing observational data analyses and numerical simulations using a mesoscale model. For both cases of 9-10 July 2008 (Case A) and 18-19 August 2006 (Case B), the heavy rainfall system developed over the western slope of the Central Mountain Range (CMR) under low-level prevailing southwesterly and westerly flows in early afternoon, respectively. These heavy rainfall systems were moving westward toward Taiwan Strait from CMR, while the embedded individual cells were moving in the opposite direction, behaving like a multicell storm. It was also found these individual cells were initiated, enhanced, and then maintained at the leading edge of the near-surface cool outflow and merged with the heavy rainfall systems which became long-lived. These heavy rainfall systems were classified as an upstream propagating precipitation system in a low Froude-number, conditionally unstable flow with high convective available potential energy (CAPE) or Regime I as proposed in a previous study.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.090
GPT teacher head0.348
Teacher spread0.258 · 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 teacher head, 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

Citations1
Published2016
Admission routes1
Has abstractyes

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