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Record W4377080259 · doi:10.5140/jass.2022.39.3.79

Thermospheric Wind Observation and Simulation during the Nov 4, 2021 Geomagnetic Storm Event

2022· article· en· W4377080259 on OpenAlexaff
Wenbin Wang, William Ward

Bibliographic record

VenueJournal of Astronomy and Space Sciences · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of New Brunswick
FundersEurostarsNuclear Safety and Security CommissionNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsGeomagnetic stormStormThermosphereAtmospheric sciencesEarth's magnetic fieldIonosphereMagnetosphereSolar windInterplanetary magnetic fieldGeologyInterplanetary spaceflightAtmosphere (unit)LatitudeClimatologyGeophysicsEnvironmental scienceMeteorologyPhysicsMagnetic fieldGeodesyOceanography

Abstract

fetched live from OpenAlex

Thermospheric wind observations from high to mid latitudes are compared with the newly developed Multiscale Atmosphere Geospace Environment (MAGE) model for the Nov 3–4 geomagnetic storm. The observation and simulation comparison shows a very good agreement and is better at high latitudes in general. We were able to identify a thermospheric poleward wind reduction possibly linked to a northward turning of the Interplanetary Magnetic Field (IMF) at ~22 UT on Nov 3 and an enhancement of the poleward wind to a southward turning near 10 UT on Nov 4 at high latitudes. An IMF southward turning may have led to an enhancement of equatorward winds at Boulder, Colorado near midnight. Simultaneous occurrence of aurora may be associated with an IMF By turning negative. The MAGE model wind simulations are consistent with observations in these cases. The results show the model can be a very useful tool to further study the magnetosphere and ionosphere coupling on short time scales.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score0.672

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 studies0.0010.000
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 head0.006
GPT teacher head0.218
Teacher spread0.211 · 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
Published2022
Admission routes1
Has abstractyes

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