HR: 10:20h
AN: SM12B-01 INVITED     [Abstracts]
TI: Prospects and Challenges of Magnetospheric Data Assimilation
AU: * Raeder, J
EM: J.Raeder@unh.edu
AF: Space Science Center, University of New Hampshire, 39 College Road, Durham, NH 03824 United States
AU: Larson, D
EM: Douglas.Larson@unh.edu
AF: Space Science Center, University of New Hampshire, 39 College Road, Durham, NH 03824 United States
AB: Data assimilation techniques are widely used in atmospheric and oceanic sciences. In fact, terrestrial weather forecasts are based on assimilative modeling. The quality of these forecasts would be significantly inferior to today's standards if the forecasts were based on either data or models alone. More recently, much progress has also been made with ionospheric assimilative models. Introducing established techniques such as Kalman filtering or variational methods (3DVAR, 4DVAR) into magnetospheric models thus appears to be straight forward. However, there are distinct differences between these systems that may limit the usefulness of these approaches for numerical magnetosphere models, for example, different time scale separations, different internal inertia, and the sensitivity of magnetosphere models to boundary conditions. In this talk we will discuss these issues and point out possible remedies, such as ensemble prediction.
DE: 2740 Magnetospheric configuration and dynamics
DE: 2753 Numerical modeling
DE: 2784 Solar wind/magnetosphere interactions
DE: 3315 Data assimilation
SC: SPA-Magnetospheric Physics [SM]
MN: Fall Meeting 2005