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Record W2904441111 · doi:10.1080/07055900.2018.1549016

An Empirical Tropical Instability Wave-induced Wind Stress Model in the Equatorial Pacific and its Incorporation into the Ocean Model

2018· article· en· W2904441111 on OpenAlexvenueno aff
Yanzhou Wei, Xianbiao Kang, Yuhua Pei

Bibliographic record

VenueATMOSPHERE-OCEAN · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsnot available
FundersChina Ocean Mineral Resources Research and Development AssociationNational Natural Science Foundation of ChinaNational Aeronautics and Space Administration
KeywordsWind stressCrosswindClimatologyCurl (programming language)Environmental scienceSea surface temperatureAtmospheric sciencesPerturbation (astronomy)MeteorologyGeologyPhysics

Abstract

fetched live from OpenAlex

Satellite observations revealed that there is a close relationship between perturbations of sea surface temperature (SST) and wind stress (τ) induced by tropical instability waves (TIWs; SSTTIW and τ TIW). Using the empirical relationship observed between TIW-induced wind stress divergence (curl) and downwind (crosswind) SST gradients, this study establishes a TIW-induced wind stress field perturbation model τ TIW = F(SST). This empirical model solves τ TIW from the TIW-induced wind stress divergence and curl, which are estimated from the downwind and crosswind SST gradients. This empirical τ TIW = F(SST) model can be incorporated into the ocean model to take into account the effect of τ TIW. By comparing two experiments with and without the τ TIW effect, this study demonstrates that τ TIW has a substantial effect on the equatorial Pacific heat budget and induces the long-term mean SST to exhibit a 0.2°C difference, which is consistent with previous studies.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.848
Threshold uncertainty score0.786

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.030
GPT teacher head0.256
Teacher spread0.226 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueATMOSPHERE-OCEANSame topicOceanographic and Atmospheric ProcessesFrench-language works237,207