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Record W4291637422 · doi:10.1002/essoar.10512147.1

Influence of The Madden-Julian Oscillation on Continental United States Hurricane Landfalls

2022· preprint· en· W4291637422 on OpenAlexafffund
Philip J. Klotzbach, Carl J. Schreck, Gilbert P. Compo, Kimberly M. Wood, Eric C. J. Oliver, Steven G. Bowen, Michael M. Bell

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsDalhousie University
FundersOffice of Naval ResearchNatural Sciences and Engineering Research Council of CanadaNational Oceanic and Atmospheric AdministrationG. Unger Vetlesen Foundation
KeywordsMadden–Julian oscillationTropical cycloneClimatologyLandfallTropical cyclone rainfall forecastingConvectionAtlantic hurricaneStormIndian oceanTropical cyclone scalesOceanographyTropical cyclogenesisSouthern HemisphereGeologyEnvironmental scienceGeographyMeteorologyCyclone (programming language)

Abstract

fetched live from OpenAlex

The Madden-Julian oscillation (MJO) significantly impacts North Atlantic hurricanes, with more hurricane activity occurring when the MJO favors enhanced convection over Africa and the tropical Indian Ocean and suppressed hurricane activity occurring when the MJO favors enhanced convection over the tropical Pacific. Using data from 1905-2015, we find more hurricanes make landfall in the continental US when the MJO enhances convection over the tropical Indian Ocean. In addition, when the MJO enhances convection over the Western Hemisphere, tropical cyclones tend to form in the Gulf of Mexico or the Caribbean, leading to more Gulf Coast landfalls. As the MJO moves to the Indian Ocean, more storms form in the tropical Atlantic, increasing the number of Florida and East Coast landfalls. The MJO’s modulation of tropical cyclone steering winds appears to be secondary to its effects on genesis locations.

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)0.000
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 score0.236
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.016
GPT teacher head0.248
Teacher spread0.231 · 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

Citations1
Published2022
Admission routes2
Has abstractyes

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