Forecasting space weather: automatic system for interplanetary shocks prediction

Kussul, NN, 1Shelestov, AYu., 2Skakun, SV, 2Zhytomirska, KG
1National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute», Kyiv, Ukraine
2Space Research Institute of the National Academy of Sciences of Ukraine and the State Space Agency of Ukraine, Kyiv, Ukraine
Kosm. nauka tehnol. 2008, 14 ;(3):039-047
Publication Language: Ukrainian
We describe the automatic system for interplanetary (IP) shocks prediction using observations from the ЕРАМ instrument onboard the ACE satellite. The proposed three-module cascade system architecture consists of IP shock onset detection module and two neural networks modules for dangerous IP shock type prediction and IP shock arrival time prediction. The proposed approach was verified on historical data of IP shocks for last solar cycle maximum (in 2000) that included both minor and moderate IP shocks and outperformed existing models.
Keywords: modules, prediction, shocks
1. Data archive of the first level of the ACE satellite. [in Ukrainian]. Available:
2. Data of the first level of the ACE satellite in real time. [in Ukrainian]. Available:
3. Classification of space weather events by NOAA. [in Ukrainian]. Available:
4. List of shock waves for 1997-2006 (IZMIRAN). [in Ukrainian]. Available: events.htm
5. Haykin S. Neural Networks: A Comprehensive Foundation, Transl. from Eng., 940 p. (Izd. dom Vil'jams, Moscow, 2006) [in Russian].
6. Shelestov A. Yu., Zhitomirskaya K. G., Kremenetsky I. A., Illin N. I. Automatic detection of interplanetary shocks based on data from ACE satellite. Kibernetika i vychislitel'naja tehnika, No. 151, 3—16 (2006) [in Russian].
7. Blais G., Metsa P. Operating the Hydro-Quebec grid under magnetic storm conditions since the storm of March 13, 1989. In: Proc. Solar-Terrestrial Predictions Workshop, Ottawa, May 18-22, 1992, Eds J. Hruska, M. A. Shea, D. F. Smart, G. Heckman, Vol. 1, 108—130 (NOAA, Boulder, USA, 1993).
8. Boaghe O. M., Balikhin M. A., Billings S. A., Alleyne H. Identification of nonlinear processes in the magnetospheric dynamics and forecasting of Dst index. J. Geophys. Lett., 106, 30047—30066 (2001).
9. Cole D. G. Space weather: Its Effects and Predictability. Space Sci. Rev., No. 107, 295—302 (2003).
10. Doherty P., Coster A. J., Murtagh W. Space weather effects of October-November 2003. GPS Solutions, 8, 267—271 (2004).
11. Dryer M., Smart D. F. Dynamical models of coronal transients and interplanetary disturbances. Adv. Space Res., 4, 291—301 (1984).
12. Fry C. D., Sun W., Deehr C. S., et al. Improvements to the HAF solar wind model for space weather predictions. J. Geophys. Res., 106 (A10), 20985—21002 (2001).
13. Igel C., Husken M. Improving the Rprop learning algorithm. In: Proceedings of the Second International Symposium on Neural Computation, Eds H. Bothe, R. Rojas, 115—121 (ICSC Academic Press, 2000).
14. Leontaritis I. J., Billings S. A. Model Selection and Validation Methods for Nonlinear Systems. Int. J. Control., 45, 311—341 (1987).
15. Riedmiller M., Braun H. A direct adaptive method for faster backpropagation learning: The RPROP algorithm. Proc. of the IEEE Intl. Conf. on Neural Networks, 586—591 (San Francisco, USA., 1993).
16. Riley P., Linker J., Mikic Z., Lionello R. MHD modeling of the solar corona and inner heliosphere: Comparison with observations. Space Weather, Eds P. Song, H. J. Singer, G. L. Siscoe. (Geophys. Monogr. Ser.), 125, 159 p. (2001).
17. Smart D. F., Shea M. A. A simplified model for timing the arrival of solarare-initiated shocks. J. Geophys. Res., 90, 183—190 (1985).
18. Smith Z. K., Dryer M., Ort E., Murtagh W. Performance of interplanetary shock prediction models. J. Atmos. Solar-Terr. Phys., 62, 1264—1274 (2000).

19. Vandegriff J., Wagstaff K., Ho G., Plauger J. Forecasting space weather: Predicting interplanetary shocks using neural networks. Adv. Space Res., 36, 2323— 2327 (2005).