Data assimilation (DA) is a powerful and versatile method for combining observational data of a system with its dynamical model to generate state estimates. These techniques are essential for numerical weather and climate predictions, but aplications of DA to many other scientific and engineering disciplines are emerging rapidly. DA is inherently interdisciplinary in nature and requires close collaborations and interactions between researchers in atmospheric sciences, in nonlinear dynamics and complex systems, and in applied mathematics and statistics.
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