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Record W4400662810 · doi:10.5194/asr-21-1-2024

Mesoscale weather influenced by auroral gravity waves contributing to conditional symmetric instability release?

2024· article· en· W4400662810 on OpenAlexaff
Paul Prikryl

Bibliographic record

VenueAdvances in science and research · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsExtratropical cycloneAtmospheric sciencesSevere weatherGravity waveInstabilityMiddle latitudesConvectionEnvironmental scienceGeologyStormGeophysicsPhysicsMeteorologyGravitational waveMechanicsAstrophysics

Abstract

fetched live from OpenAlex

Abstract. We consider possible influence on severe weather occurrence in the context of solar wind coupling to the magnetosphere–ionosphere–atmosphere system, mediated by aurorally excited atmospheric gravity waves. Solar wind high-speed streams from coronal holes cause intensifications of ionospheric currents at high latitudes launching gravity waves propagating in the upper and lower atmosphere. While these gravity waves reach the troposphere with much attenuated amplitudes, they can contribute to conditional symmetric instability release and intensification of storms. Severe weather events, including winter storms and heavy rainfall causing floods and flash floods, show a tendency to follow arrivals of solar wind high-speed streams from coronal holes. The ERA5 re-analysis is used to evaluate slantwise convective available potential energy and vertically integrated extent of realizable symmetric instability to assess the likelihood of slantwise convection in frontal zones of extratropical cyclones during severe snowstorms and flash floods. The observed low-level southerly winds and high wind shears in these regions are favorable conditions for over-reflection of down-going aurorally excited gravity waves potentially contributing to conditional symmetric instability release leading to slantwise convection and high-rate precipitation.

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)0.003
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.011
GPT teacher head0.349
Teacher spread0.338 · 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 designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

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