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On the Role of the Last Closed Drift Shell and ULF-Wave Radial Diffusion in Driving Fast and Repeatable Radiation Belt Electron Loss

2023· article· en· W4389271834 on OpenAlexaff
L. Olifer, I. R. Mann, L. G. Ozeke, S. G. Claudepierre, Dan Baker, H. E. Spence, Steven K. Morley

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadiation Effects in Electronics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsVan Allen radiation beltElectronDiffusionRadiationPhysicsComputational physicsShell (structure)Aerospace engineeringGeophysicsGeologyMaterials scienceOpticsNuclear physicsEngineeringPlasma

Abstract

fetched live from OpenAlex

Dynamics of relativistic and ultra-relativistic electrons, trapped in the Earth's Van Allen radiation belts, have been actively studied since their discovery over 50 years ago.However, properly characterizing fast changes in electron flux during geomagnetic storms remains a significant challenge for accurately modeling their behavior.In this study, we show how magnetopause shadowing losses, enhanced by outward Ultra-Low Frequency (ULF) wave radial diffusion, can deplete the radiation belt electron fluxes within hours or even minutes, causing long-lasting impacts on the subsequent, post-dropout, belt dynamics.By resolving four geomagnetic storms with fast radiation belt losses using high spatial and temporal resolution electron flux data from the constellation of Global Positioning System (GPS) satellites we reveal a very strong correspondence between the location of the magnetopause, characterized by the location of the last closed drift shell (LCDS), and the loss patterns of trapped electrons in each storm.We generalize the results of these case studies by statistically analyzing seven years of data from the entire Van Allen Probes mission in the context of the LCDS and how these losses are much more organized, repeatable, and therefore potentially predictable than previously thought.We reveal that the electron loss propagates in a similar manner from one storm to the next, depleting the radiation belt electron flux by almost the same energy-dependent factor, with respect to the pre-storm redaction belt content, in every event.Combining this LCDS shadowing model with an energy-dependent ULF wave radial diffusion model, we show how such a similar and repeatable fractional loss of the pre-storm electron population in each storm can be reproduced and explained.This is especially important since underestimates of the loss intensity can also create over-estimated and unrealistic flux levels in models.This phantom electron radiation can lead to the prediction of an overly harsh radiation environment.More accurate characterization of fast and repeatable magnetopause shadowing losses, reported here, may therefore be used to improve radiation belt specification and forecast model accuracy.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score0.369

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)0.0000.000

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 head0.002
GPT teacher head0.175
Teacher spread0.172 · 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 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
Published2023
Admission routes1
Has abstractyes

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