Using a neural network to make operational forecasts of ionospheric variations and storms at Kokubunji, Japan

An operational model was developed for forecasting ionospheric variations and storms at Kokubunji (35⊙N, 139⊙E), 24 hours in advance, by using a neural network. The ionospheric critical frequency (foF2) shows periodic variabilities from days to the solar cycle length and also shows sporadic changes known as ionospheric storms caused by geomagnetic storms (of solar disturbance origin). The neural network was trained for the target parameter of foF2 at each local time and input parameters of solar flux, sunspot number, day of the year, Kindex at Kakioka. The training was conducted using the data obtained for the period from 1960 to 1984. The method was validated for the period from 1985 to 2003. The trained network can be used for daily forecasting ionospheric variations including storms using prompt daily reports of K-index, sunspot number, and solar flux values available on-line.

[1]  D. F. Martyn The morphology of the ionospheric variations associated with magnetic disturbance I. Variations at moderately low latitudes , 1953, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences.

[2]  S. Matsushita A study of the morphology of ionospheric storms , 1959 .

[3]  T. Yonezawa Theory of formation of the ionosphere , 1966 .

[4]  H. Rishbeth,et al.  The origin of storm increases of mid-latitude F-layer electron concentration , 1971 .

[5]  N. Matuura Theoretical models of ionospheric storms , 1972 .

[6]  H. Rishbeth,et al.  Field-aligned and field-perpendicular velocities in the ionospheric F2-layer , 1978 .

[7]  Geoffrey E. Hinton,et al.  Learning representations by back-propagating errors , 1986, Nature.

[8]  Geoffrey E. Hinton,et al.  Learning representations by back-propagation errors, nature , 1986 .

[9]  Geoffrey E. Hinton,et al.  Learning representations of back-propagation errors , 1986 .

[10]  Ken-ichi Funahashi,et al.  On the approximate realization of continuous mappings by neural networks , 1989, Neural Networks.

[11]  V. Tikhomirov On the Representation of Continuous Functions of Several Variables as Superpositions of Continuous Functions of one Variable and Addition , 1991 .

[12]  D. Bilitza,et al.  International Reference Ionosphere - Past, Present, Future , 1993 .

[13]  L. Bossy,et al.  International Reference Ionosphere: Past, present, and future. I - Electron density. II - Plasma temperatures, ion composition and ion drift , 1993 .

[14]  S. Hyakin,et al.  Neural Networks: A Comprehensive Foundation , 1994 .

[15]  Lee-Anne Williscroft,et al.  Neural networks, foF2, sunspot number and magnetic activity , 1996 .

[16]  L. R. Cander,et al.  Neural networks in ionospheric prediction and short-term forecasting , 1997 .

[17]  Ersin Tulunay,et al.  Temporal and spatial forecasting of ionospheric critical frequency using neural networks , 1999 .

[18]  Lj.R. Cander,et al.  Short-Term Prediction of foF2 using Time-Delay Neural Network , 1999 .

[19]  Peter Wintoft,et al.  Ionospheric foF2 storm forecasting using neural networks , 2000 .

[20]  J. Nazuno Haykin, Simon. Neural networks: A comprehensive foundation, Prentice Hall, Inc. Segunda Edición, 1999 , 2000 .

[21]  G. D. Chemistry of the thermosphere and ionosphere , 2002 .

[22]  W. Wan,et al.  Modeling investigation of ionospheric storm effects over Millstone Hill during August 4–5, 1992 , 2004 .

[23]  Lee-Anne McKinnell,et al.  Predicting the ionospheric F layer using neural networks , 2004 .

[24]  N. Barkhatov Forecasting of the critical frequency of the ionosphereF2 layer by the method of artificial neural networks , 2004 .

[25]  L. McKinnell,et al.  On the global model for foF2 using neural networks , 2005 .

[26]  L. Libin,et al.  Forecasting of Ionospheric Critical Frequency Using Neural Networks , 2005, Chinese Journal of Space Science.

[27]  Lee-Anne McKinnell,et al.  On the global short‐term forecasting of the ionospheric critical frequency foF2 up to 5 hours in advance using neural networks , 2005 .

[28]  T. Maruyama,et al.  Ionospheric responses to the October 2003 superstorm: Longitude/local time effects over equatorial low and middle latitudes , 2007 .