Forecast of the daily geomagnetic perturbations

1Stodilka, MI
1Astronomical Observatory of the Ivan Franko National University of L’viv, L'viv, Ukraine
Kosm. nauka tehnol. 2010, 16 ;(5):46-53
https://doi.org/10.15407/knit2010.05.046
Publication Language: Ukrainian
Abstract: 
A model of the robust forecast of geomagnetic perturbations is constructed and tested. Some ways to improve the forecast are considered. The correlation coefficient between daily observed and forecasted data is greater than 0.9. Our procedure can be used to perform the forecast of the daily geomagnetic and planetary indices during both moderate and superhigh solar activity.
Keywords: geomagnetic perturbations, planetary index, solar activi ty
References: 
1. Tikhonov A. N., Arsenin V. Ya. Methods of Solution of Ill-Posed Problems, 142 p. (Nauka, Moscow, 1979) [in Russian].
2. Hemming R.V. Digital Filters, 224 p. (Sov. Radio, Moscow, 1980) [in Russian].
3. Amata E., Consolini G., Pallocchia G., Marcucci M. ANN forecast of hourly averaged AE index based on L1 IMF and plasma measurements. Acta Geophysica, 57 (1), 185—196 (2009).
https://doi.org/10.2478/s11600-008-0083-1 
4. Cid C., Saiz E., Cerrato Y. Physical models to forecast the Dst index: A comparison of results. In: Connecting Sun and Heliosphere: Proc. of the Solar Wind 11 / SOHO 16, Workshop, 601—604 (2005).
5. Eselevich V. G., Fainshtein V. G. An investigation of the relationship between the magnetic storm Dst-index and different types of solar wind streams. Ann. Geophys., 11 (8), 678—684 (1993).
6. Eselevich V. G., Fainshtein V. G., Rudenko G. V., et al. Forecasting the velocity of quasi-stationary solar wind and the intensity of geomagnetic disturbances produced by it. Cosmic Res., 47 (2), 95—113 (2009).
https://doi.org/10.1134/S0010952509020026 
7. Gonzalez W. D., Echer E. A study on the peak Dst and peaknegative Bz relationship during intense geomagnetic storms. Geophys. Res. Lett., 32, 18103— 18106 (2005).
https://doi.org/10.1029/2005GL023486 
8. Gonzalez W. D., Tsurutani B. T., Gonzalez A. L. Interplanetary origin of geomagnetic storms. Space Sci. Rev., 88, 529—562 (1999).
https://doi.org/10.1023/A:1005160129098 
9. Kane R. P. How good is the relationship of solar and interplanetary plasma parameters with geomagnetic storms? J. Geophys. Res., 110, 2213— 2215 (2005).
https://doi.org/10.1029/2004JA010799 
10. Khabarova O. V. Current problems of magnetic storm prediction and possible ways of their solving. Sun and Geosphere, 2 (1), 33—38 (2007).
11. King J. H., Papitashvili N. E. Solar wind spatial scales in and comparisons of hourly Wind and ACE plasma and magnetic field data. J. Geophys. Res., 110A (2), A02104—A02111 (2005).
https://doi.org/10.1029/2004JA010649 
12. Lundstedt H., Gleisner H., Wintoft P. Operational forecasts of the geomagnetic Dst index. Geophys. Res. Lett., 29 (24), 2181—2184 (2002).
https://doi.org/10.1029/2002GL016151 
13. O’Brien T. P., McPherron R. L. Forecasting the ring current index Dst in real time. J. Atmos. Terr. Phys., 62, 1295—1299 (2000).
https://doi.org/10.1016/S1364-6826(00)00072-9 
14. Pallocchia G., Amata E., Consolini G., et al. Geomagnetic Dst index forecast based on IMF data only. Ann. Geophys., 24, 989—999 (2006).
https://doi.org/10.5194/angeo-24-989-2006 
15. Parnowski A. S. Regression modeling method of space weather prediction. Astrophys. and Space Sci., 323 (2), 169—180 (2009).
https://doi.org/10.1007/s10509-009-0060-4 
16. Siscoe G., McPherron R. L., Liemohn M. W., et al. Reconciling prediction algorithms for Dst. J. Geophys. Res., 110A (2), A02215—A02222 (2005).
17. Temerin M., Li X. A new model for the prediction of Dst on the basis of the solar wind. J. Geophys. Res., 107A (12), 1472—1479 (2002).
18. Temerin M., Li X. Dst model for 1995—2002. J. Geophys. Res., 111A (4), A04221 — A04231 (2006).
19. Wang C. B., Chao J. K., Lin C. H. Influence of the solar wind dynamic pressure on the decay and injection of the ring current. J. Geophys. Res., 108A (9), 1341—1351 (2003).
https://doi.org/10.1029/2003JA009851 
20. Wu J., Lundstedt H. Geomagnetic storm predictions from solar wind data with the use of dynamic neural networks. J. Geophys. Res., 102A (7), 14255—14268 (1997).
https://doi.org/10.1029/97JA00975 

21. Yermolaev Y. I., Yermolaev M. Y., Zastenker G. N., et al. A. Statistical studies of geomagnetic storm dependencies on solar and interplanetary events: a review. Planet. Space Sci., 53, 189—196 (2005).
https://doi.org/10.1016/j.pss.2004.09.044