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Record W2605252493 · doi:10.1175/jcli-d-16-0711.1

SynthETC: A Statistical Model for Severe Winter Storm Hazard on Eastern North America

2017· article· en· W2605252493 on OpenAlexaboutno aff
Tim Hall, James F. Booth

Bibliographic record

VenueJournal of Climate · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsnot available
FundersNational Aeronautics and Space Administration
KeywordsNorth Atlantic oscillationClimatologyStormEl Niño Southern OscillationTropical cycloneAtlantic multidecadal oscillationAtlantic hurricaneEnvironmental scienceGeographyOceanographyGeology

Abstract

fetched live from OpenAlex

We develop, evaluate, and apply "SynthETC," a statistical-stochastic model of winter extra-tropical cyclones (ETCs) over eastern North America. SynthETC simulates the life cycle of ETCs from formation to termination, and it can be used to estimate the probability of extreme ETC events beyond the historical record. Two modes of climate variability are used as independent covariates: El Niño/Southern Oscillation (ENSO) Niño3.4 and the monthly North Atlantic Oscillation (NAO). We use SynthETC to estimate the annual occurrence rate over sites in eastern North America of intense ETC passage in different ENSO and NAO states. Positive NAO is associated with increased rates over the North Atlantic, while negative NAO is associated with decreased rates over the North Atlantic and increased rates over northern Quebec. Positive ENSO is associated with decreased rates over the North Atlantic, Ontario, and the Canadian Maritime, while negative ENSO is associated with increased rates over those regions, as well as the Great Lakes 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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score0.645

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.301
Teacher spread0.261 · 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

Citations21
Published2017
Admission routes1
Has abstractyes

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