A Community Terrain-Following Ocean Modeling System (ROMS/TOMS) [report]

Hernan G. Arango
2007 unpublished
LONG-TERM GOALS The long-term technical goal is to design, develop and test the next generation primitive equation, Terrain-following Ocean Modeling System (TOMS) for high-resolution scientific and operational applications. This project will improve the ocean modeling capabilities of the U.S. Navy for relocatable, coastal, coupled atmosphere-ocean forecasting applications. It will also benefit the ocean modeling community at large by providing the current state-of-the-art knowledge in physics,
more » ... umerical schemes, and computational technology. OBJECTIVES The main objective is to produce a tested expert Terrain-following Ocean Modeling System for scientific and operational applications over a wide range of spatial (coastal to basin) and temporal (days to seasons) scales. The primary focus is to implement the most robust set of options and algorithms for relocatable coastal forecasting systems nested within basin-scale operational models for the Navy. The system includes some of the analysis and prediction tools that are available in Numerical Weather Prediction (NWP), like 4-Dimensional Variational (4DVar) data assimilation, ensemble prediction, adaptive sampling, and circulation stability and sensitivity analysis. APPROACH The framework for TOMS is based on ROMS because of its accurate and efficient numerical algorithms, tangent linear and adjoint models, variational data assimilation, modular coding and explicit parallel structure conformal to modern computer architectures (both cache-coherent sharedmemory and distributed cluster technologies). Currently, both ROMS and TOMS are identical and continue improving and evolving. ROMS remains as the scientific community model while TOMS becomes the operational community model. ROMS/TOMS is a three-dimensional, free-surface, terrain-following ocean model that solves the Reynolds-averaged Navier-Stokes equations using the hydrostatic vertical momentum balance and Boussinesq approximation (Haidvogel et al. 2000; Shchepetkin and McWilliams, 2005) . The governing dynamical equations are discretized on a vertical coordinate that depend on the local water depth. The horizontal coordinates are orthogonal and curvilinear allowing Cartesian, spherical, and polar spatial discretization on an Arakawa C-grid. Its dynamical kernel includes accurate and efficient algorithms for time-stepping, advection, pressure gradient McWilliams 2003, 2005),
doi:10.21236/ada573073 fatcat:x3rjgjepmrc3ll62vxgcf2r63m