Open AccessModeling and prediction of global magnetic disturbance in near‐Earth space: A case study for K p index using NARX models
Author(s) -
Ayala Solares Jose Roberto,
Wei HuaLiang,
Boynton R. J.,
Walker Simon N.,
Billings Stephen A.
Publication year - 2016
Publication title -
space weather
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.254
H-Index - 56
ISSN - 1542-7390
DOI - 10.1002/2016sw001463
Subject(s) - nonlinear autoregressive exogenous model , autoregressive model , earth's magnetic field , index (typography) , nonlinear system , disturbance (geology) , space weather , control theory (sociology) , computer science , magnetosphere , meteorology , environmental science , econometrics , mathematics , artificial intelligence , physics , geology , magnetic field , control (management) , paleontology , world wide web , quantum mechanics
Severe geomagnetic disturbances can be hazardous for modern technological systems. The reliable forecast of parameters related to the state of the magnetosphere can facilitate the mitigation of adverse effects of space weather. This study is devoted to the modeling and forecasting of the evolution of the K p index related to global geomagnetic disturbances. Throughout this work the Nonlinear Autoregressive with Exogenous inputs (NARX) methodology is applied. Two approaches are presented: (i) a recursive sliding window approach and (ii) a direct approach. These two approaches are studied separately and are then compared to evaluate their performances. It is shown that the direct approach outperforms the recursive approach, but both tend to produce predictions slightly biased from the true values for low and high disturbances.