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Record W2281567183 · doi:10.1002/2015gl067050

What would happen to Superstorm Sandy under the influence of a substantially warmer Atlantic Ocean?

2016· article· en· W2281567183 on OpenAlexaboutno aff
William K. M. Lau, Jian Shi, Weichen Tao, Keun-Yong KIM

Bibliographic record

VenueGeophysical Research Letters · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsnot available
FundersPacific Northwest National LaboratoryNASA HeadquartersNational Aeronautics and Space AdministrationU.S. Department of Energy
KeywordsExtratropical cycloneStormClimatologyLandfallMiddle latitudesOceanographyClockwiseNova scotiaEnvironmental scienceLatitudeGeologyRotation (mathematics)

Abstract

fetched live from OpenAlex

Abstract Based on ensemble numerical simulations, we find that possible responses of Sandy‐like superstorms under the influence of a substantially warmer Atlantic Ocean bifurcate into two groups. In the first group, storms are similar to present‐day Sandy from genesis to extratropical transition, except they are much stronger, with peak Power Destructive Index (PDI) increased by 50–80%, heavy rain by 30–50%, and maximum storm size (MSS) approximately doubled. In the second group, storms amplify substantially over the interior of the Atlantic warm pool, with peak PDI increased by 100–160%, heavy rain by 70–180%, and MSS more than tripled compared to present‐day Superstorm Sandy. These storms when exiting the warm pool, recurve northeastward out to sea, subsequently interact with the developing midlatitude storm by mutual counterclockwise rotation around each other and eventually amplify into a severe Northeastern coastal storm, making landfall over the extreme northeastern regions from Maine to Nova Scotia.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.036
GPT teacher head0.293
Teacher spread0.257 · 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

Citations22
Published2016
Admission routes1
Has abstractyes

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