Modeling oceanic multiphase flow by using Lagrangian particle tracking

Abstract:

While the density of seawater is basically determined by its temperature, salinity and pressure, the effective density becomes higher when the water mass contains suspended sediment. On the other hands, effective density declines when water mass contains fine scale materials of lower density such as bubbles and ice crystals. Such density anomaly induced by small scale materials suspended in water masses sometimes plays important roles in the sub-mesoscale ocean physics. To simulate these small scale oceanic multiphase flow, a new modeling framework using an online Lagrangian particle tracking method is developed. A Lagrangian particle tracking method has substantial advantages such as an explicit treatment of buoyancy force acting on each individual particle, no numerical diffusion and dissipation, high dynamic range and an ability to track the history and each individual particle. However, its numerical cost causes difficulty when we try to simulate a large number of particles. In the present study we implement a numerically efficient particle tracking scheme using linked-list data structure, which is coupled with a nonhydrostatic dynamical core. This newly developed model successfully reproduces characteristics of some interesting small scale multiphase processes, for example hyperpycnal flow (a sediment-rich river water plume trapped at ocean floor) and grease ice cover (a slurry mixture of frazil ice crystals and seawater).