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A scheme for forecasting severe space weather

2020· article· en· W3089567104 on OpenAlexaboutno aff
N. Balan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsnot available
Fundersnot available
KeywordsSpace weatherPhysicsShock (circulatory)MeteorologyEnvironmental scienceInternal medicineMedicine

Abstract

fetched live from OpenAlex

We have developed and tested a scheme for forecasting severe space weather (SvSW) that caused all known electric power outages and telecommunication system failures since 1957 and the Carrington event of 1859. The SvSW events of 04 August 1972 has puzzled the scientific community as it occurred during a moderate storm (DstMin = -124 nT) while all other SvSW events occurred during super storms (DstMin ≤ -250 nT). The solar wind velocity V and IMF Bz measured by ACE satellite at the L1 point since 1998 are used. For the earlier SvSW events such as the Carrington event of 1859, Quebec event of 1989, and the events in February 1958 and August 1972 we used the information from the literature. The coincidence of high ICME front (or shock) velocity ΔV (sudden increase in V over the background by over 275 km/s) and sufficiently large Bz southward at the time of the ΔV increase is associated with SvSW; and their product (ΔV×Bz) is found to exhibit a large negative spike at the speed increase. Such a product (ΔV×Bz) exceeding a threshold seems suitable for forecasting SvSW, with a maximum forecasting time of 35 minutes using ACE data. However, the coincidence of high V (not containing ΔV) and large Bz southward does not correspond to SvSW, indicating the importance of the impulsive action of high ΔV and large Bz southward coming through when they coincide. The need for the coincidence is verified using the CRCM.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.031
GPT teacher head0.215
Teacher spread0.184 · 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 source (direct Gemma or distilled Codex), 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
Published2020
Admission routes1
Has abstractyes

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