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Record W3129593971 · doi:10.1175/mwr-d-20-0306.1

Synoptic–Dynamic and Airmass Characteristics Distinguishing Long- and Short-Duration Freezing Rain Events in the South-Central United States

2021· article· en· W3129593971 on OpenAlexaff
Christopher D. McCray, John R. Gyakum, Eyad H. Atallah

Bibliographic record

VenueMonthly Weather Review · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMeteorological Phenomena and Simulations
Canadian institutionsMcGill University
Fundersnot available
KeywordsTrough (economics)ClimatologyAdvectionSynoptic scale meteorologyForcing (mathematics)PrecipitationAtmospheric sciencesEnvironmental scienceGeologyMeteorologyGeography

Abstract

fetched live from OpenAlex

Abstract Though prolonged freezing rain events are rare, they can result in substantial damage when they occur. While freezing rain occurs less frequently in the south-central United States than in some regions of North America, a large number of extremely long-duration events lasting at least 18 h have been observed there. We explore the key synoptic–dynamic conditions that lead to these extreme events through a comparison with less severe short-duration events. We produce synoptic–dynamic composites and 7-day backward trajectories for parcels ending in the warm and cold layers for each event category. The extremely long-duration events are preferentially associated with a deeper and more stationary 500-hPa longwave trough centered over the southwestern United States at event onset. This trough supports sustained flow of warm, moist air from within the planetary boundary layer over the Gulf of Mexico northward into the warm layer. The short-duration cases are instead characterized by a more transient upper-level trough axis centered over the south-central U.S. region at onset. Following event onset, rapid passage of the trough leads to quasigeostrophic forcing for descent and the advection of cold, dry air that erodes the warm layer and ends precipitation. While trajectories ending in the cold layer are very similar between the two categories, those ending in the warm layer have a longer history over the Gulf of Mexico in the extreme cases compared with the short-duration ones, resulting in warmer and moister onset warm layers.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.301

Codex and Gemma teacher scores by category

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

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 head0.025
GPT teacher head0.246
Teacher spread0.221 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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