8-12 July 2013
Particle flux forecast using space wind parameters in a multivariate auto-regressive model with Kalman filtering
Presented by Ms. Charlotte HILLEBRAND on 9 Jul 2013 from 11:10 to 11:30
Type: Oral Presentation
Session: Space Science
Track: Track D2 - Space Science
Particles from the solar wind penetrate into the Earth's radiation belts where they can have a detrimental effect on the operation and lifetimes of satellites as well as influencing terrestrial communications and power lines. Forecasting conditions in the solar wind is thus an important problem. Previously this has been approached with various techniques including Kalman filtering and neural networks. We combine a Kalman filter with a multivariate autoregressive model based on pertinent features of the solar wind. In line with the findings of Sakaguchi et al (2013) this is expected to provide superior forecasting of solar wind conditions.
Dr Andrew B. Collier email@example.com University of KwaZulu-Natal