The ability to assimilate data into models/simulations has been shown to be critical when dealing with complex systems such as weather. The Earth's magnetosphere forms part of the space weather system, and it is necessary that data assimilation techniques be developed for magnetospheric simulations. This project will investigate two approaches to magnetospheric data assimilation. The first is a statistical regression method termed 'optimal interpolation' and the second approach is Kalman filtering.
