This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 58
Type: Topic Contributed
Date/Time: Sunday, August 1, 2010 : 4:00 PM to 5:50 PM
Sponsor: WNAR
Abstract - #308223
Title: Characterization of Space Weather Triggering Signals in Highly Variable Temporal Data: Challenges and Solutions
Author(s): Tia Lerud*+
Companies: University of Washington
Address: , Seattle, WA, 98115,
Keywords: wavelet analysis ; linear regression ; space weather ; time-series

Space weather events can threaten the lives astronauts and inflict costly damage on satellites and earth-based structures leading to communication interruptions, blackouts and environmental hazards. The triggering and development of these space weather events is not well understood. A classification system based on event characteristics and solar wind conditions is developed, in order to assist in the systematic study of these events. The challenges of identifying triggers include a time lag between the explanatory signal data and the response measurement at earth, separation of signal from noise, testing similarity of signals for different events, and the high time variability in each explanatory variable. Strategies used include wavelet analysis, conversion of signal characteristics to scores, and linear regression to predict event intensity and assess classification scheme.

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