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Record W2277027043 · doi:10.1002/2016gl067730

Surface temperature dependence of tropical cyclone‐permitting simulations in a spherical model with uniform thermal forcing

2016· article· en· W2277027043 on OpenAlexafffund
Timothy M. Merlis, Wenyu Zhou, Isaac M. Held, Ming Zhao

Bibliographic record

VenueGeophysical Research Letters · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsMcGill University
FundersCompute CanadaU.S. Department of Energy
KeywordsConvectionSpherical geometryForcing (mathematics)Tropical cycloneRadiative transferAtmospheric sciencesRadiative coolingSea surface temperatureThermalRadiative equilibriumPhysicsGeologyClimatologyEnvironmental scienceGeometryMechanicsMeteorologyMathematics

Abstract

fetched live from OpenAlex

Abstract Tropical cyclone (TC)‐permitting general circulation model simulations are performed with spherical geometry and uniform thermal forcing, including uniform sea surface temperature (SST) and insolation. The dependence of the TC number and TC intensity on SST is examined in a series of simulations with varied SST. The results are compared to corresponding simulations with doubly periodic f ‐plane geometry, rotating radiative convective equilibrium. The turbulent equilibria in simulations with spherical geometry have an inhomogenous distribution of TCs with the density of TCs increasing from low to high latitudes. The preferred region of TC genesis is the subtropics, but genesis shifts poleward and becomes less frequent with increasing SST. Both rotating radiative convective equilibrium and spherical geometry simulations have decreasing TC number and increasing TC intensity as SST is increased.

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)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.030
GPT teacher head0.282
Teacher spread0.252 · 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

Citations67
Published2016
Admission routes2
Has abstractyes

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