Abstract
Abstract. 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 Bz 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 Bz. The model is almost independent of the solar wind magnetic field Bz, except at times when Bz is exceptionally large or when the overall activity is low. On the contrary, the model shows a strong dependence on Bz at all times.
Highlights
The Earth’s magnetosphere is a dynamic system that responds to changes in the upstream solar wind
In this work we have studied the prediction of the 10-min variation of the local ground magnetic field, the 10-min RMS X and Y
By studying the solar wind data for other L1spacecraft (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
Summary
The Earth’s magnetosphere is a dynamic system that responds to changes in the upstream solar wind. In Gleisner and Lundstedt (2001b) a model was developed that predicts the 10-min average local geomagnetic field using solar wind data. In the work by Weigel et al (2002) models were developed that predict the average absolute value of B with a temporal resolution of 30 min They studied the north-south component of the magnetic field, i.e. It was found that the RMS data can be used to estimate the power spectra of X and Y This is useful for the subsequent analysis, for example, computing GIC, as both amplitude and scale (frequency) are available. Another issue is that the RMS data captures a major fraction of the variance in X.
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