A Formula for Calculating Dst Injection Rate from Solar Wind Parameters

  • Marubashi, K. (Solar and Space Weather Research Group, Korea Astronomy and Space Science Institute) ;
  • Kim, K.H. (School of Space Research, Kyung Hee University) ;
  • Cho, K.S. (Solar and Space Weather Research Group, Korea Astronomy and Space Science Institute) ;
  • Rho, S.L. (Solar and Space Weather Research Group, Korea Astronomy and Space Science Institute) ;
  • Park, Y.D. (Solar and Space Weather Research Group, Korea Astronomy and Space Science Institute)
  • Published : 2009.10.15

Abstract

This is an attempt to improve a formula to predict variations of geomagnetic storm indices (Dst) from solar wind parameters. A formula which is most widely accepted was given by Burton et al. (1975) over 30 years ago. Their formula is: dDst*/dt = Q(t) - Dst*(t)/$\tau$, where Q(t) is the Dst injection rate given by the convolution of dawn-to-dusk electric field generated by southward solar wind magnetic field and some response function. However, they did not clearly specify the response function. As a result, misunderstanding seems to be prevailing that the injection rate is proportional to the dawn-to-dusk electric field. In this study we tried to determine the response function by examining 12 intense geomagnetic storms with minimum Dst < -200 nT for which solar wind data are available. The method is as follows. First we assume the form of response function that is specified by several time constants, so that we can calculate the injection rate Q1(t) from the solar wind data. On the other hand, Burton et al. expression provide the observed injection rate Q2(t) = dDst*/dt + Dst*(t)/$\tau$. Thus, it is possible to determine the time constants of response function by a least-squares method to minimize the difference between Q1(t) and Q2(t). We have found this simple method successful enough to reproduce the observed Dst variations from the corresponding solar wind data. The present result provides a scheme to predict the development of Dst 30 minutes to 1 hour in advance by using the real time solar wind data from the ACE spacecraft.

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