Physics
Scientific paper
Dec 2003
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2003agufmsm42e..05h&link_type=abstract
American Geophysical Union, Fall Meeting 2003, abstract #SM42E-05
Physics
2700 Magnetospheric Physics, 2736 Magnetosphere/Ionosphere Interactions, 2740 Magnetospheric Configuration And Dynamics, 2799 General Or Miscellaneous
Scientific paper
The physics network model called WINDMI for the solar WIND driven Magnetosphere-Ionosphere weather system is calibrated on substorm databases [1] using a genetic algorithm. We report on the use of the network as a digital filter to classify the substorms into three types; a process traditionally performed individual inspection. We then turn to using the filter on the seven Geospace Environmental Modeling (GEM) Storms designated for community wide study. These storms cover periods of days and contain many substorms. First the WINDMI model is run with the 14 parameters set from the study based on the Blanchard-McPherron database of 117 isolated substorms with 80% of the data having the AL below -500nT. In contrast, the GEM storms have long periods with AL in the range of -1000nT. The prediction error measured with the average-relative variance (ARV) is of approximately unity. Reapplying the genetic algorithm the parameters shift such that the one long storm has an ARV=0.59. Physics modifications of the basic WINDMI model including the injection of sheet plasma into the ring current are being evaluated in terms of their impact on the ARV and comparisons with non-physics based signal processing prediction filters. Ensembles of initial conditions are run with 700MHz G3 CPU run times of order 17 sec per orbit per day of real data. The AMD AthlonXP 1700+ processor takes 5sec per orbit per day. The IBM SP-2 speed will be reported. With such speeds it is possible to run balls of initial conditions.
Substrom Classification with the WINDMI Model, W. Horton, R.S. Weigel, D. Vassiliadis, and I. Doxas, Nonlinear Processes in Geophysics, 1-9, 2003.
This work was supported by the National Science Foundation Grant ATM-0229863.
Doxas Isidoros
Horton Wendell
Mithaiwala Manish
Siebert S.
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