Data assimilation (DA) aims at accurate re-analysis, estimation and prediction of an unknown, true state by merging observed information into a model. This issue arises in all scientific areas that enjoy a profusion of data. The problem is fundamental yet challenging as it does not naturally afford a clean solution. The issue of assimilating data into models arises in all scientific areas that enjoy a profusion of data. In its broadest sense, it is the subject that arises at the meeting point of data and models. The development of effective data assimilation methods must now be viewed as one of the fundamental challenges in scientific prediction.

During the spring semster 2005, the Statistical and Applied Mathematical Sicences Instutite (SAMSI) hosted a DA program whose goal was to identify outstanding mathematical and statistical issues and challenges of geophysical data assimilation while exploring innovative approaches and new directions from an interdisciplinary perspective.