HR: 09:15h
AN: NG31A-06    [Abstracts]
TI: Space Weather Forecasting and Risk Assessment
AU: * Sharma, A
EM: ssh@astro.umd.edu
AF: Department of Astronomy, University of Maryland, College Park, MD 20742, United States
AU: Veeramani, T
EM: tmani@umd.edu
AF: Department of Electrical and Computer Engineering, University of Maryland, College Park, MD 20742, United States
AU: Chen, J
EM: chenjian@astro.umd.edu
AF: Department of Astronomy, University of Maryland, College Park, MD 20742, United States
AB: Space weather hazards are driven mainly by the turbulent solar wind, which is monitored continuously by spacecraft at the Lagrange L1 point. The correlated database of the solar wind \– magnetosphere system has been used to develop forecasting tools based on nonlinear dynamical approaches. The magnetosphere however is inherently multiscale in nature and dynamical or deterministic forecasts are possible only in a mean field sense. The deviations from the deterministic forecasts are due to the multiscale features and can be forecast only in a statistical manner. The database has been used to compute conditional probabilities following a Bayesian approach. This combination of the deterministic and probabilistic techniques yields space weather forecasts and quantitative assessments of the risks. These techniques have been applied to the forecasting of substorms (Ukhorskiy et al., GRL, 2004; Chen et al., JGR, 2006) and relativistic electron intensity in the radiation belt (Ukhorskiy et al., GRL, 2004). The multiscale property underlying the distribution of extreme events are analyzed using the burst and waiting time distributions, which are combinations of a power law with an exponential cut-off and a log-normal function (Freeman et al., GRL, 2000). The distribution of scales in the magnetosphere deviates from the power law and shows a scaling in the waiting-time distribution with respect to the mean waiting-time, characteristic of long-term correlations (Bunde et al.,PRL, 2005). However this scaling has a dependence on the threshold, leading to a rescaled distribution that deviates from a stretched exponential. The implications of these features to risk assessment analysis will be presented.
DE: 2784 Solar wind/magnetosphere interactions
DE: 2790 Substorms
DE: 3245 Probabilistic forecasting (3238)
DE: 4468 Probability distributions, heavy and fat-tailed (3265)
DE: 4475 Scaling: spatial and temporal (1872, 3270, 4277)
SC: Nonlinear Geophysics [NG]
MN: 2007 Fall Meeting