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Record W2330446505 · doi:10.2166/wqrjc.2012.111

Storm-induced circulation in the Pearl River Estuary of China during super Typhoon Koryn

2012· article· en· W2330446505 on OpenAlexafffund
Liqun Tang, Jinyu Sheng, Cai Y

Bibliographic record

VenueWater Quality Research Journal · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsDalhousie University
FundersLloyd's RegisterChina Institute of Water Resources and Hydropower ResearchNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsTyphoonEstuaryHydrographyStormDownscalingClimatologyMesoscale meteorologyBuoyEnvironmental scienceWind stressGeologyWind speedOcean currentOceanographyClimate change

Abstract

fetched live from OpenAlex

This study presents a numerical investigation of storm-induced circulation and hydrographic distributions over the Pearl River Estuary (PRE) in South China's Guangdong Province during super Typhoon Koryn in June 1993. The nested-grid modelling system used in this study has three downscaling subcomponents: an outer-most sub-model with a coarse horizontal resolution of ∼7 km for simulating surface elevations and depth-mean currents forced by wind and tides over China Seas from Bohai Sea to the northern South China Sea; and an inner-most sub-model with a fine resolution of ∼1.2 km for simulating the three-dimensional estuarine circulation and hydrographic distributions in the PRE and adjacent waters. A parametric vortex is inserted into the coarse-resolution (0.5°) numerical weather forecast products to better represent the atmospheric pressure and wind stress associated with Koryn. Model results demonstrate that large surface elevations and intense surface currents are generated over the area of influence of the storm. Lagrange velocities of near-surface particles are also used to examine the effect of the storm on the movements and dispersion of near-surface particles over the study region.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.136
GPT teacher head0.364
Teacher spread0.228 · 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.

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

Citations8
Published2012
Admission routes2
Has abstractyes

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