Application In Prediction The Geomagnetic Storm With Variation Characteristics Cosmic Ray

In all kinds of events which affect the space weather, geomagnetic storm is one of the main reasons to make the failure of space disasters. The geomagnetic storm is formed by uneven structure of interplanetary space acting on the geomagnetic field. Cosmic ray flux will be changed when charged particles pass through these structures, which becomes a precursor of strong geomagnetic storms. In this paper, cosmic ray was applied to analyze geomagnetic storms, using different methods to extract the characteristic parameters of geomagnetic storms.In the second chapter, variation of cosmic rays was introduced as a preparation for the forecast. Cosmic ray neutron data on the same time each day of Oulu, Beijing and Southpole stations. It is found cosmic ray flux shows regular diurnal variation, the maximum value at 14:00, and the minimum value at 2:00. This feature was also found by many researchers. It is first discovered Southpole station also exists the daily variation of cosmic ray flux characteristics. The maximum value appears at 17:00 UT. Data of energetic proton flux of GOES satellite and cosmic ray neutrons are fitted. The fitting result shows cosmic ray neutrons and energetic proton have correlation. Thus cosmic rays can reflect the energetic proton, and be used to analyze the change of space environment to achieve the purpose of forecasting the geomagnetic storm.Cosmic ray is influenced by uneven structure of interplanetary. CME can be perceived by the impending changes of cosmic ray. An algorithm is introduced to use the cosmic ray neutron detector data to predict great geomagnetic storms. The connection between cosmic ray and great geomagnetic storms and the relationship between cosmic ray stations are qualitatively analyzed. The neutron detector data from Irkutsk and Oulu stations are employed and wavelet diagnosing technology is used to improve the stability of the data. It is found that under the same conditions of universal time the correlation of the two stations is higher than quiet days when geomagnetic disturbs, while under the same local time its the contrary. Thus the variation in disturbed time and quiet time can be used to predict geomagnetic storms. The algorithm is specifically used to analyze the geomagnetic storm events in July 2004. It is found before geomagnetic storm relative fluxes of cosmic rays of Irkutsk and Oulu became different. It can be used as a precursor of strong geomagnetic storms. Statistics with all relative events during Mar.2001 to May 2005 support an appropriate threshold related to the relative difference of cosmic ray about strong geomagnetic storms. It is tested with all events during Sept.2005 to Dec.2011 with the threshold. The result turned out to be encouraging with the accuracy rate reach to 87.5%(7 out of 8) and false forecast rate reach to 35.7%(5 out of 14).During cosmic ray closing to the Earth propagation path will be disturbed by local strong magnetic field region. Parameters of fluctuation characteristic can be extracted to predict the arrival of CME. Morlet wavelet is applied to analyze the character of cosmic ray intensity of Beijing station (latitude:40.04° N, longitude: 116.4°E, China) before and after great magnetic storm and three conclusions were derived. Firstly,24h periodicity exists and is distinct during quiet time. The module of Morlet wavelet of 12h periodicity is stability less than 0.6. Secondly, to analyze the spectrum variation of wavelet before and after great geomagnetic storm on 25th July,2004 with a 90-days window, we found the power spectrum is significantly enhanced in the low frequency, and can even reach the period of 16-days. After further research, fluctuation of 12h periodicity becomes stronger a few hours to one day before strong geomagnetic storm. It is tested with all events in 2002,2004 and 2005. And finally, rapid increase in module of Morlet wavelet may be a precursor of great magnetic storm that great geomagnetic storm would occur when module reaches a threshold. After analyzing Morlet wavelet module of 12h periodicity and doing some statistics with all the great geomagnetic events in 2002,2004 and 2005, the threshold is set to be 0.6. The method is tested with the all events in 2003. The result turned out to be encouraging that 5 out of 6 (83%) great geomagnetic storms could be predicted and time in advance was plenty, which proved to be the candidate of prediction algorithm for great geomagnetic storm.