Journal of Tropical Oceanography ›› 2018, Vol. 37 ›› Issue (4): 9-9.doi: 10.11978/2017105CSTR: 32234.14.2017105

Special Issue: 南海专题

• Orginal Article • Previous Articles     Next Articles

An Argo trajectory simulation system for the South China Sea using Lagrangian method*

Tianyu WANG1,2(), Yan DU1,2(), Yifan XIA1,2   

  1. 1. State Key Laboratory of Tropical Oceanography (South China Sea Institute of Oceanology, Chinese Academy of Sciences), Guangzhou 510301, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China;
  • Received:2017-09-28 Revised:2017-11-19 Online:2018-07-20 Published:2018-07-16
  • Supported by:
    National Natural Science Foundation of China (41525019, 41521005);“Global Changes and Air-Sea Interaction” of State Oceanic Administration (GASI-IPOVAI-02);Strategic Priority Research Program of the Chinese Academy of Sciences (XDA11010103)

Abstract:

Our Argo trajectory simulation system for the South China Sea (SCS) contains the high-resolution ambient velocity field, a Lagrangian particle tracking model and the parameterization that represents the vertical motions of profiling Argo floats. This system is applied to simulate both conventional Argo floats (typically parked at 1000 m depth and profiling to 2000 m depth) and Deep Argo floats (parked at 500 m above the seafloor) within the SCS. By conducting the simulation with the counterparts of six core Argo floats serviced in the SCS, we find the displacements of synthetic floats from the simulation system resemble the real float displacements over 100-day time intervals. We therefore judge the simulations for core Argo are robust and further apply the system to simulate a potential Deep Argo array (with the resolution of 2°×2°×30 day). The results explore both the representativeness and the predictability of float displacements, which may provide a basis to understand float displacements in the deep layer as well as to contribute to planning deep Argo array program.

Key words: Argo, Lagrangian trajectory, the South China Sea

CLC Number: 

  • P714.3