Open AccessImpact of Horizontal Resolution (Submesoscale Permitting vs. Mesoscale Resolving) on Ocean Dynamic Features in the South China Sea
Author(s) -
Wu Renhao,
Jia Liqun,
Li Chunyan,
Liu Yu,
Han Bo,
Chen Dake
Publication year - 2022
Publication title -
earth and space science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.843
H-Index - 23
ISSN - 2333-5084
DOI - 10.1029/2022ea002448
Subject(s) - baroclinity , mesoscale meteorology , barotropic fluid , climatology , geology , horizontal resolution , ocean surface topography , ocean current , terrain , oceanography , meteorology , geography , cartography
Model resolution is a key factor that impacts the model bias in simulating ocean dynamics. How would model resolution influence model bias is an important question. In this study, we set up two sets of experiments with identical settings except the grid resolution, one with a minimum spacing of 2 km, referred to as the submesoscale permitting (SP) model, and the other with a minimum spacing of 6 km, referred to as the mesoscale resolving (MR) model, to investigate the impact of horizontal resolution on simulated dynamic features in the South China Sea. Results show that the SP outperforms the MR model in simulating both barotropic and baroclinic tides, upper ocean circulation, sea surface height, and temperature in the South China Sea, and in simulating the evolution of the eddy pair east of Indo‐China Peninsula in summer and the Kuroshio loop current in the Luzon Strait in winter. The SP model also performs better in simulating thermal structure within the ocean and the winter mixed layer depth. Additionally, the SP model can capture more vertical motion features. The superiority of the SP model lies in its ability to better resolve terrain features that have a significant impact on ocean dynamical processes, and to resolve more physical processes. As a result, the SP model relies less on the uncertain parameterized processes. Our study has important implications for studies on the modeling of physical oceanography in the South China Sea, as well as for the reduction of climate model biases.