Entry Date:
August 21, 2017

Multiscale Data Assimilation

Principal Investigator Pierre Lermusiaux

Ocean modeling is the process of developing and utilizing theoretical and computational models for the understanding and prediction of ocean dynamics. Data assimilation is the process of quantitatively estimating dynamically evolving fields by combining information from observations with those predicted by models, ideally respecting nonlinear dynamics and capturing non-Gaussian features, without heuristics or ad hoc approximations. Even though ocean dynamics often involve multiple scales, the theory for rigorous multiscale data assimilation is still in its infancy. The present project is to research next-generation multiscale data assimilation, with a focus on shelfbreak regions, including non-hydrostatic effects.