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Record W4392577258 · doi:10.5194/egusphere-egu24-12721

It's Not Easy Being Green: Quantitative Modeling of STEVE's Picket Fence Emissions Driven by Local Parallel Electric Fields

2024· preprint· en· W4392577258 on OpenAlexaff
L. Claire Gasque, Reza Janalizadeh, Brian J. Harding, M. T. Gillies, J. D. Yonker

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicGreen IT and Sustainability
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPicketingFence (mathematics)Electric fieldPhysicsTelecommunicationsPolitical scienceEngineeringMathematicsLawCombinatoricsQuantum mechanics

Abstract

fetched live from OpenAlex

The vibrant green streaks of the 'picket fence' typically appear below a STEVE arc in the subauroral sky, at lower latitudes than the auroral oval. Recent studies suggest that, despite its aurora-like appearance, the picket fence may not be driven by magnetospheric particle precipitation but instead by local electric fields parallel to Earth's magnetic field. In this study, we investigate this hypothesis by quantitatively comparing observed picket fence optical spectra with emissions generated in a kinetic model driven by parallel electric fields in a realistic neutral atmosphere. We find that sufficiently large parallel electric fields can reproduce the observed ratio of N2 first positive to oxygen green line emissions, without producing N2+ first negative emissions. We find that, at a typical picket fence altitude of 110 km, parallel electric fields between 40 and 70 Td (~80 to 150 mV/m at 110 km) result in calculated spectral features consistent with observed ones, providing a benchmark for future observational and modeling studies. Additionally, we review studies which have identified similar features to the picket fence in the aurora, suggesting that a similar mechanism may be at work there. Since visible and ultraviolet auroral emissions are increasingly used to infer magnetospheric activity, it is important to better understand and quantify potential sources of emission beyond particle 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.827
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.002
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 head0.020
GPT teacher head0.267
Teacher spread0.247 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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