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Mathematics Group

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 and combustion models.