首页> 美国政府科技报告 >Development and Utilization of Regional Oceanic Modeling System (ROMS). Delicacy, Imprecision, and Uncertainty of Oceanic Simulations: An Investigation with the Regional Oceanic Modeling System (ROMS). Mixing in the Ocean Surface Layer Using the Regional Oceanic Modeling System (ROMS)
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Development and Utilization of Regional Oceanic Modeling System (ROMS). Delicacy, Imprecision, and Uncertainty of Oceanic Simulations: An Investigation with the Regional Oceanic Modeling System (ROMS). Mixing in the Ocean Surface Layer Using the Regional Oceanic Modeling System (ROMS)

机译:区域海洋模拟系统(ROms)的开发与利用。海洋模拟的精细,不精确和不确定性:区域海洋模拟系统(ROms)的调查。使用区域海洋建模系统(ROms)在海洋表面层混合

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Our core objectives are code improvements and oceanographic simulation studies with the Regional Oceanic Modeling System (ROMS). The targeted problems are submesoscale wakes, fronts, and eddies; nearshore currents; internal tides; regional and Pacific eddy-resolving circulations and their low-frequency variability; mesoscale ocean-atmosphere coupling; and planetary boundary layers with surface gravity waves. To address these problems we are making ROMS more of a multi-process, multi-purpose, multi-scale model by including the coupling of the core circulation dynamics to surface gravity waves; sediment resuspension and transport; biogeochemistry and ecosystems; non- hydrostatic large-eddy simulation; and mesoscale atmospheric circulation, and by providing a framework for data-assimilation analyses (led by others). Our major algorithmic objectives are cross-scale grid-embedding in turbulent flows; improved accuracy in the Boussinesq approximation with a realistic Equation of State (EOS); accurate advection; dynamically adaptive, vertical coordinates; surface-wave-averaged vortex force and Lagrangian transport; and parameterization of wave-breaking and other mixing effects. Finally, we continue to further improve the pre- and post-processing tools and on-line documentation for ROMS. A parallel objective is to establish the characteristics of model uncertainty in ROMS for realistic simulation of complex flows, as an intrinsic model contribution to analysis and to forecast errors. The premise is that defensible alternative model designs -- in parameter values, subgrid-scale parameterizations, resolution, algorithms, topography, and forcing data -- may often provide a range of answers comparable to the model-measurement discrepancies, although as yet this kind of sensitivity is largely undocumented. A corollary is that alternative models may have a sizable degree of mutually irreproducible answers for complex flows.

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