scholarly journals Three-Dimensional Unstructured Grid Finite-Volume Model for Coastal and Estuarine Circulation and Its Application

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2752
Author(s):  
Jun Lee ◽  
Jungwoo Lee ◽  
Sang-Leen Yun ◽  
Seog-Ku Kim
Keyword(s):  
Finite Volume ◽  
Unstructured Grid ◽  
Finite Difference Methods ◽  
Three Dimensional ◽  
Circulation Model ◽  
Ocean Model ◽  
Estuarine Circulation ◽  
Computational Grids ◽  
Time Step ◽  
Advection Term

We developed a three-dimensional unstructured grid coastal and estuarine circulation model, named the General Ocean Model (GOM). Combining the finite volume and finite difference methods, GOM achieved both the exact conservation and computational efficiency. The propagation term was implemented by a semi-implicit numerical scheme, the so-called θ scheme, and the time-explicit Eulerian–Lagrangian method was used to discretize the nonlinear advection term to remove the major limitation of the time step, which appears when solving shallow water equations, by the Courant–Friedrichs–Lewy stability condition. Because the GOM uses orthogonal unstructured computational grids, allowing both triangular and quadrilateral grids, considerable flexibility to resolve complex coastal boundaries is allowed without any transformation of governing equations. The GOM was successfully verified with five analytical solutions, and it was also validated when applied to the Texas coast, showing an overall skill value of 0.951. The verification results showed that the algorithm used in GOM was correctly coded, and it is efficient and robust.

scholarly journals An Unstructured Grid, Finite-Volume Coastal Ocean Model (FVCOM) System

Oceanography ◽  
2006 ◽  
Vol 19 (1) ◽  
pp. 78-89 ◽  
Author(s):  
Changsheng Chen ◽  
Roberet Beardsley ◽  
Geoffrey Cowles
Keyword(s):  
Finite Volume ◽  
Unstructured Grid ◽  
Coastal Ocean ◽  
Ocean Model ◽  
Coastal Ocean Model

scholarly journals Can Lagrangian Tracking Simulate Tracer Spreading in a High-Resolution Ocean General Circulation Model?

2019 ◽  
Vol 49 (5) ◽  
pp. 1141-1157 ◽  
Author(s):  
Patrick Wagner ◽  
Siren Rühs ◽  
Franziska U. Schwarzkopf ◽  
Inga Monika Koszalka ◽  
Arne Biastoch
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Circulation Model ◽  
Eddy Diffusivity ◽  
Ocean General Circulation Model ◽  
Horizontal Resolution ◽  
Ocean Model ◽  
Time Step ◽  
Lagrangian Particles ◽  
Cape Basin

AbstractTo model tracer spreading in the ocean, Lagrangian simulations in an offline framework are a practical and efficient alternative to solving the advective–diffusive tracer equations online. Differences in both approaches raise the question of whether both methods are comparable. Lagrangian simulations usually use model output averaged in time, and trajectories are not subject to parameterized subgrid diffusion, which is included in the advection–diffusion equations of ocean models. Previous studies focused on diffusivity estimates in idealized models but could show that both methods yield similar results as long as the deformations-scale dynamics are resolved and a sufficient amount of Lagrangian particles is used. This study compares spreading of an Eulerian tracer simulated online and a cloud of Lagrangian particles simulated offline with velocities from the same ocean model. We use a global, eddy-resolving ocean model featuring 1/20° horizontal resolution in the Agulhas region around South Africa. Tracer and particles were released at one time step in the Cape Basin and below the mixed layer and integrated for 3 years. Large-scale diagnostics, like mean pathways of floats and tracer, are almost identical and 1D horizontal distributions show no significant differences. Differences in vertical distributions, seen in a reduced vertical spreading and downward displacement of particles, are due to the combined effect of unresolved subdaily variability of the vertical velocities and the spatial variation of vertical diffusivity. This, in turn, has a small impact on the horizontal spreading behavior. The estimates of eddy diffusivity from particles and tracer yield comparable results of about 4000 m2 s−1 in the Cape Basin.

scholarly journals WAVETRISK-1.0: an adaptive wavelet hydrostatic dynamical core

2019 ◽  
Author(s):  
Nicholas K.-R. Kevlahan ◽  
Thomas Dubos
Keyword(s):  
Shallow Water ◽  
General Circulation ◽  
Wave Train ◽  
Shallow Water Equation ◽  
Three Dimensional ◽  
Circulation Model ◽  
Time Step ◽  
Adaptive Wavelet ◽  
Dynamical Core ◽  
Vertical Coordinate

Abstract. This paper presents the new adaptive dynamical core wavetrisk. The fundamental features of the wavelet-based adaptivity were developed for the shallow water equation on the β-plane in Dubos and Kevlahan (2013) and extended to the icosahedral grid on the sphere in Aechtner et al. (2015). The three-dimensional dynamical core solves the compressible hydrostatic multilayer rotating shallow water equations on a multiscale dynamically adapted grid. The equations are discretized using a Lagrangian vertical coordinate version of dynamico introduced in Dubos et al. (2015). The horizontal computational grid is adapted at each time step to ensure a user-specified relative error in either the tendencies or the solution. The Lagrangian vertical grid is remapped using an adaptive Lagrangian-Eulerian (ALE) algorithm onto the initial hybrid σ pressure-based coordinates as necessary. The resulting grid is adapted horizontally, but uniform over all vertical layers. Thus, the three-dimensional grid is a set of columns of varying sizes. The code is parallelized by domain decomposition using mpi and the variables are stored in a hybrid data structure of dyadic quad trees and patches. A low storage explicit fourth order Runge-Kutta scheme is used for time integration. Validation results are presented for three standard dynamical core test cases: mountain-induced Rossby wave train, baroclinic instability of a jet stream and the Held and Suarez simplified general circulation model. The results confirm good strong parallel scaling and demonstrate that wavetrisk can achieve grid compression ratios of several hundred times compared with an equivalent static grid model.

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