Welcome to the IOM Web Site @ Arizona State University

This modular system, known as the `Inverse Ocean Modeling system' or `IOM' (Chua and Bennett, 2001) is based on a twenty-year effort. From a control theory perspective, IOM effects fixed-interval smoothing of nonlinear dynamics and nonlinear observing processes. The dynamics may be weak constraints; as a result, the number of computational degrees may be very large. From a statistical perspective, IOM minimizes the estimator of maximum likelihood for random errors in the dynamics and data. IOM makes such large, nonlinear but functionally smooth optimization problems feasible by iterating on the nonlinearities, yielding linear smoothing problems, and by making preconditioned searches in the `data subspace' at each iterate. The system is in the process of being optimized for several computer architectures.

The IOM has already been implemented in an unsophisticated way with a variety of models of the ocean and the coupled ocean-atmosphere. These experiences have demonstrated that developing, optimizing and maintaining the code for IOM or a similar system is so expensive a task that most ocean modelers are unwilling to undertake it. One purpose of this project is to make the IOM available to a range of well supported ocean models that are already in, or are entering into, widespread use. Furthermore, similar techniques are implemented in operational weather forecasting and ocean forecasting, in ocean biogeochemistry, in groundwater hydrology and in solid-earth geophysics. Thus the IOM will also be useful to, and made available to, the entire geosciences community.

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