Scientifc rationale

Data assimilation is a powerful analysis method in which observed information is accumulated into dynamical models taking into account physical constraints and properties. This approach makes possible efficient and accurate estimations of physical properties which cannot be observed directly, and obtain better understanding of the underlying physics and develop forecast models. It has provided major advances in ocean and atmospheric science and meteorology, but has not been used for studying dynamical processes on the Sun. We propose an international team of solar physicists, observers and modelers, and experts in data assimilation methods to develop initial applications of the data assimilation methods to key solar physics problems of the internal dynamics and magnetic field generation and transport, using data from the SOHO space mission and ground-based observatories. One important application of the new methodology is prediction of the strength of the solar cycle.