Physics – Geophysics
Scientific paper
Dec 2002
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2002georl..29x..34l&link_type=abstract
Geophysical Research Letters, Volume 29, Issue 24, pp. 34-1, CiteID 2181, DOI 10.1029/2002GL016151
Physics
Geophysics
13
Magnetospheric Physics: Forecasting, Magnetospheric Physics: Solar Wind/Magnetosphere Interactions, Mathematical Geophysics: Nonlinear Dynamics, Magnetospheric Physics: Storms And Substorms
Scientific paper
We here present a model for real time forecasting of the geomagnetic index Dst. The model consists of a recurrent neural network that has been optimized to be as small as possible without degrading the accuracy. It is driven solely by hourly averages of the solar wind magnetic field component Bz, particle density n, and velocity V, which means that the model does not rely on observed Dst. In an evaluation based on more than 40,000 hours of solar wind and Dst data, it is shown that this model has smaller errors than other models currently in operational use. A complete description of the model is given in an appendix.
Gleisner Hans
Lundstedt Henrik
Wintoft Peter
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