Prediction of the Dst index from solar wind parameters by a neural network method

Details Prediction of the Dst index from solar wind parameters by a neural network method Prediction of the Dst index from solar wind parameters by a neural network method

Dec 2002

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2002ep%26s...54.1263w&link_type=abstract

Earth, Planets and Space, Volume 54, p. 1263-1275.

Other

5

Scientific paper

Using the Elman-type neural network technique, operational models are constructed that predict the Dst index two hours in advance. The input data consist of real-time solar wind velocity, density, and magnetic field data obtained by the Advanced Composition Explorer (ACE) spacecraft since May 1998 (http://www2.crl.go.jp/uk/uk223/service/nnw/index.html). During the period from February to October 1998, eleven storms occurred with minimum Dst values below -80 nT. For ten of these storms the differences between the predicted minimum Dst and the minimum Dst calculated from ground-based magnetometer data were less than 23%. For the remaining one storm (beginning on 19 October 1998) the difference was 48%. The discrepancy is likely to stem from a imperfect correlation between the solar wind parameters near ACE and those near the earth. While the IMF Bz remains to be the most important parameter, other parameters do have their effects. For instance, Dst appears to be enhanced when the azimuthal direction of IMF is toward the sun. A trapezoid-shaped increase in the solar wind density enhances the main phase Dst by almost 10% compared with the case of no density increase. Velocity effects appear to be stronger than the density effects. Our operational models have, in principle, no limitations in applicability with respect to storm intensity.

Affiliated with

Also associated with

No associations

Rating

Prediction of the Dst index from solar wind parameters by a neural network method does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Prediction of the Dst index from solar wind parameters by a neural network method, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Prediction of the Dst index from solar wind parameters by a neural network method will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-963218