predictability of geomagnetic series

predictability of geomagnetic series

;E. Bellanger;V. G. Kossobokov;V. G. Kossobokov;J.-L. Le Mouël
journal of food measurement and characterization 2003 Vol. 21 pp. 1101-1109
137
bellanger2003annalespredictability

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)

Citation

ID: 238269
Ref Key: bellanger2003annalespredictability
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
238269
Unique Identifier:
10.5194/angeo-21-1101-2003
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet