Explorer of the Seas
About the Model
The Regional Ocean Modeling System (ROMS) is used for data assimilation and ocean prediction in the Intra-Americas Sea (IAS) with particular emphasis on the Caribbean Sea. The investigators on this research team include: Hernan G. Arango (Rutgers University), Andrew M. Moore, Brian Powell (University of California, Santa Cruz), Ralph F. Milliff (Colorado Research Associates Division) and Julio Sheinbaum (CICESE). Arango and Moore, in collaboration with Cornuelle (Scripps Institution of Oceanography), Di Lorenzo (Georgia Institute of Technology) and Miller (Scripps Institution of Oceanography), have recently developed 4-Dimensional, VARiational (4DVAR) data assimilation tools for ocean state estimation in ROMS. Both strong and weak constraint methods will be used in the IAS to meld model and observations to estimate initial conditions for real-time prediction onboard the Explorer of the Seas. In the weak constraint form, the 4DVAR formalism takes explicit account of uncertainties in ocean model and surface forcing in finding an optimal solution to fit model dynamics with remote and in-situ observations. The development of these tools was a substantial undertaking and contribution in its own right, but the ultimate payoff will come from new oceanographic insights gained through the efficient use of the 4DVAR tools in a variety of settings.
The IAS provides a non-trivial testbed, and an opportunity to address outstanding physical oceanographic issues regarding transport pathways, and mesoscale variability in a vital sub-domain of the world ocean. The IAS is the source of the Gulf Stream system and moisture from the IAS is the primary source of precipitation over much of the eastern and central continental United States. In addition, the IAS circulation exerts a strong influence on the formation and propagation of tropical depressions and hurricanes that threaten the United States and Caribbean nations.
The IAS is characterized by an interesting and complex dynamical structure, and is relatively rich in observational data (see Figure below). The Antilles island arc and Sverdrup dynamics of the interior North Atlantic impose strict inflow boundary conditions on the region, making the IAS an ideal laboratory for inverse modeling and data assimilation studies, as noted previously by Roemmich (1981, 1983) and Wunsch and Grant 1982). We propose to revisit this problem using 4DVAR inverse methods. The objectives and scientific goals of the proposed research are:
- To develop a real-time data assimilation and prediction system for the IAS based on a continuous upper ocean monitoring system;
- To demonstrate, as a proof of concept, the utility of (i) in a real-time, sea-going environment, and demonstrate the value of collecting routine ocean observations from specially equipped ocean vessels, in this case cruise liners;
- To develop much needed experience in both the assimilation of disparate ocean data and ocean prediction in regional ocean models.