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Assimilating ocean and geophysics data

A key problem in many sciences is data assimilation- using a model (maybe an uncertain model) and data (maybe noisy data) to assess the state of a system. Our work on implicit sampling makes it possible to produce sample states that have a consistently high probability, reducing by a large factor the exploratory computing that needs to be done to eliminate unlikely possibilities. This is a major breakthrough. We have applied the new methods to problems that range from determining the biological state of oceans, to analyzing data about the earth’s magnetic field, to analyzing combustion models.