A layered numerical model for simulating the generation and propagation of internal tides over continental slope

Du Tao; Fang Guo-hong; Fang Xin-hua

doi:10.1007/BF02842710

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A layered numerical model for simulating the generation and propagation of internal tides over continental slope

Updated：2023-05-16

- A layered numerical model for simulating the generation and propagation of internal tides over continental slope
- Journal of Oceanology and Limnology Vol. 17, Issue 2, Pages: 125-131(1999)
- Affiliations：
  
  1. Institute of Oceanology Chinese Academy of Sciences
  2. Physical Oceanography Institute Ocean University of Qingdao
- Author bio：
- Funds：
- DOI：10.1007/BF02842710
  CLC：
- Published：1999
- Accepted：
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Tao, D., Guo-hong, F. & Xin-hua, F. A layered numerical model for simulating the generation and propagation of internal tides over continental slope., Chin. J. Ocean. Limnol. 17, 125–131 (1999). https://doi.org/10.1007/BF02842710
DOI：

Tao, D., Guo-hong, F. & Xin-hua, F. A layered numerical model for simulating the generation and propagation of internal tides over continental slope., Chin. J. Ocean. Limnol. 17, 125–131 (1999). https://doi.org/10.1007/BF02842710 DOI：

摘要

Abstract

A layered three-dimensional nonlinear numerical model was constructed to simulate the generation and propagation of internal tides over the continental slope. The simulation was split into external mode computation (EMC) and internal mode computation (IMC) to minimize the computational load. IMC was carried out once after EMC was implemented N times. As to EMC

a semi-implicit numerical scheme was applied in such a way that the pressure gradient terms and the velocity divergence terms were discretized semi-implicitly

but the other terms were discretized explicitly. Eulerian-Lagrangian explicit discretization was applied to the convective terms simultaneously. As a result

the stability of EMC did not depend on the wave celerity and time step was not limited by the CFL condition. More than that

use of the conjugate gradient accelerated Jacobi method further improved the computational efficiency of the model.

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references

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