Predictions of local ground geomagnetic field fluctuations during the 7-10 November 2004 events studied with solar wind driven models

The 7-10 November 2004 period contains two events for which the local ground magnetic field was severely disturbed and simultaneously, the solar wind displayed several shocks and negative B z periods. Using empirical models the 10-min RMS and at Brorfelde (BFE, 11.67° E, 55.63° N), Denmark, are predicted. The models are recurrent neural networks with 10-min solar wind plasma and magnetic field data as inputs. The predictions show a good agreement during 7 November, up until around noon on 8 November, after which the predictions become significantly poorer. The correlations between observed and predicted log RMS is 0.77 during 7-8 November but drops to 0.38 during 9-10 November. For RMS the correlations for the two periods are 0.71 and 0.41, respectively. Studying the solar wind data for other L1-spacecraft (WIND and SOHO) it seems that the ACE data have a better agreement to the near-Earth solar wind during the first two days as compared to the last two days. Thus, the accuracy of the predictions depends on the location of the spacecraft and the solar wind flow direction. Another finding, for the events studied here, is that the and models showed a very different dependence on B z . The model is almost independent of the solar wind magnetic field B z , except at times when B z is exceptionally large or when the overall activity is low. On the contrary, the model shows a strong dependence on B z at all times.

[1]  A. Nishida.  Geomagnetic diagnosis of the magnetosphere , 1978 .

[2]  Antti Pulkkinen,et al.  Time derivative of the horizontal geomagnetic field as an activity indicator , 2001 .

[3]  G. Siscoe,et al.  Characteristic magnetic field and speed properties of interplanetary coronal mass ejections and their sheath regions , 2005 .

[4]  Antti Pulkkinen,et al.  Fast computation of the geoelectric field using the method of elementary current systems and planar Earth models , 2004 .

[5]  J. Richardson,et al.  The main features of solar wind plasma correlations of importance to space weather strategy , 2002 .

[6]  D. Vassiliadis,et al.  Coupling of the solar wind to temporal fluctuations in ground magnetic fields , 2002 .

[7]  Peter Wintoft,et al.  Study of the solar wind coupling to the time difference horizontal geomagnetic field , 2005 .

[8]  Louis J. Lanzerotti,et al.  Statistical identification of solar wind origins of magnetic impulse events , 2003 .

[9]  P. Wintoft,et al.  Operational forecasts of the geomagnetic Dst index , 2002 .

[10]  Risto Pirjola,et al.  Review On The Calculation Of Surface Electric And Magnetic Fields And Of Geomagnetically Induced Currents In Ground-Based Technological Systems , 2002 .

[11]  A. Mavretic,et al.  SWE, a comprehensive plasma instrument for the WIND spacecraft , 1995 .

[12]  D. Baker,et al.  Dst index prediction using data‐derived analogues of the magnetospheric dynamics , 1998 .

[13]  M. Acuna,et al.  The ACE Magnetic Fields Experiment , 1998 .

[14]  W. Gonzalez,et al.  Geoeffectiveness of interplanetary shocks, magnetic clouds, sector boundary crossings and their combined occurrence , 2004 .

[15]  D. H. Boteler,et al.  Assessment of Geomagnetic Hazard to Power Systems in Canada , 2001 .

[16]  Joshua A. Paquette,et al.  Solar wind measurements with SOHO: The CELIAS/MTOF proton monitor , 1998 .

[17]  Todd R. Ogden,et al.  Wavelet Methods for Time Series Analysis , 2002 .

[18]  J. Phillips,et al.  Geomagnetic activity associated with earth passage of interplanetary shock disturbances and coronal mass ejections , 1991 .

[19]  H. Koskinen,et al.  Variability of magnetospheric storms driven by different solar wind perturbations , 2002 .

[20]  D. Baker,et al.  The Dst geomagnetic response as a function of storm phase and amplitude and the solar wind electric field , 1999 .

[21]  J. W. Griffee,et al.  Solar Wind Electron Proton Alpha Monitor (SWEPAM) for the Advanced Composition Explorer , 1998 .

[22]  Thomas R. Detman,et al.  Review of techniques for magnetic storm forecasting , 2013 .

[23]  Henrik Lundstedt,et al.  Neural network modeling of solar wind‐magnetosphere interaction , 1997 .

[24]  E. Cliver,et al.  Sources of geomagnetic activity during nearly three solar cycles , 2002 .

[25]  H. Gleisner,et al.  Auroral electrojet predictions with dynamic neural networks , 2001 .

[26]  Henrik Lundstedt,et al.  A neural network-based local model for prediction of geomagnetic disturbances , 2001 .

[27]  Norman F. Ness,et al.  The ACE Magnetic Fields Experiment , 1998 .

[28]  P. Mayaud,et al.  Derivation, Meaning, and Use of Geomagnetic Indices , 1980 .

[29]  Peter Wintoft,et al.  Real time Kp predictions from solar wind data using neural networks , 2000 .

[30]  David Boteler,et al.  The effects of geomagnetic disturbances on electrical systems at the earth's surface , 1998 .

[31]  H. W. Kroehl,et al.  What is a geomagnetic storm , 1994 .

[32]  Daniel N. Baker,et al.  Statistical analyses in the study of solar wind-magnetosphere coupling , 1985 .