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Record W2338018350 · doi:10.1002/2016ja022664

Solar activity variability in the IRI at high latitudes: Comparisons with GPS total electron content

2016· article· en· W2338018350 on OpenAlexafffundabout
David R. Themens, P. T. Jayachandran

Bibliographic record

VenueJournal of Geophysical Research Space Physics · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space AgencyNew Brunswick Innovation FoundationUniversity of Bern
KeywordsTECTotal electron contentIonosondeEquinoxIonosphereEnvironmental scienceDaytimeAtmospheric sciencesLatitudeGeodesyGeologyElectron densityPhysicsElectronGeophysics

Abstract

fetched live from OpenAlex

Abstract Total electron content (TEC) measurements from 10 dual‐frequency GPS receivers in the Canadian High Arctic Ionospheric Network (CHAIN) are used to evaluate the performance of International Reference Ionosphere (IRI)‐2007 within the Canadian sector. Throughout the region, we see systematic underestimation of daytime TEC, particularly at solar maximum, where summer and equinox root‐mean‐square errors reach as high as 14 total electron content units, 1 TECU = 10 16 el m −2 (TECU). It is also shown that the use of a monthly IG index, in place of the IRI's standard IG12 index, leads to an improvement in TEC specification by up to 3 TECU in the polar cap and up to 6 TECU in the subauroral region during periods of short‐term, large amplitude changes in solar activity. On diurnal timescales, variability in TEC is found to be underestimated by the IRI, during equinox periods, by up to 40% at subauroral latitudes and up to 70% in the polar cap region. During the winter, diurnal variations are overestimated by up to 40% in the subauroral region and are underestimated within the polar cap by up to 80%. Using collocated ionosonde data, we find IRI bottomside TEC to be within 1 TECU of observation with errors largest during the equinoxes. For the topside we find good agreement during the winter but significant underestimation of topside TEC by the IRI during summer and equinox periods, exceeding 6 TECU at times. By ingesting measured N m F 2 into the IRI, we show that the topside thickness parameterization is the source of the bulk of the observed TEC errors.

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)0.002
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 score0.533
Threshold uncertainty score0.485

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
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 head0.033
GPT teacher head0.307
Teacher spread0.274 · 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

Citations42
Published2016
Admission routes3
Has abstractyes

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