predictability of geomagnetic series
Clicks: 140
ID: 238269
2003
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
30.0
/100
140 views
17 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #177 of 484 articles by views in journal of food measurement and characterization
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 484 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
The aim of this paper is
to lead a practical, rational and rigorous approach concerning what can be
done, based on the knowledge of magnetic series, in the field of prediction of
the extreme geomagnetic events. We compare the magnetic vector differential at
different locations computed with different resolutions, from an entire day to
minutes. We study the classical correlations and the simplest possible
prediction scheme to conclude a high level of predictability of the magnetic
vector variation. The results obtained are far from a random guessing: the
error diagrams are either comparable with earthquake prediction studies or
out-perform them when the minute sampling is used in accounting for hourly
magnetic vector variation. We demonstrate how the magnetic extreme events can
be predicted from the hourly value of the magnetic variation with a lead time
of several hours. We compute the 2-D empirical distribution of consecutive
values of the magnetic vector variation for the estimation of conditional
probabilities of different types. The achieved results encourage further
development of the approach to prediction of the extreme geomagnetic events.
Key words. Ionosphere (modeling and forecasting) – Magnetospheric physics (storms and substorms)
Key words. Ionosphere (modeling and forecasting) – Magnetospheric physics (storms and substorms)
| Reference Key |
bellanger2003annalespredictability
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;E. Bellanger;V. G. Kossobokov;V. G. Kossobokov;J.-L. Le Mouël |
| Journal | journal of food measurement and characterization |
| Year | 2003 |
| DOI |
10.5194/angeo-21-1101-2003
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.