Feature Extraction and Classification of Substorms

Details Feature Extraction and Classification of Substorms Feature Extraction and Classification of Substorms

May 2001

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2001agusm..sm61b10w&link_type=abstract

American Geophysical Union, Spring Meeting 2001, abstract #SM61B-10

Physics

2722 Forecasting, 2784 Solar Wind/Magnetosphere Interactions, 2788 Storms And Substorms

Scientific paper

The need to understand both the global filter properties and the limits of predictability inherent in the magnetosphere--ionosphere system is important for constructing spatiotemporal predictions of ionospheric activity. Low--order dynamic models provide a concise description in terms of a nonlinear filter that couples the solar wind to ionospheric currents. We compare the trigger mechanisms and nonlinearities of these filters and show that the most sensitive element is the trigger timing. Several forms of data driven triggers, based on solar wind conditions and energy loaded into the magnetosphere, are compared. The possibility of using a low--order model to determine what part of a ground based magnetometer time series is due to characteristics of the solar wind driver and what part is due to internal dynamics of the M--I system is considered. This method is compared with a neural network classification scheme constructed to extract predictable features from substorm magnetometer time series.

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