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论文题目  Deep-Current Intraseasonal Variability Interpreted as Topographic Rossby Waves and Deep Eddies in the Xisha Islands of the South China Sea 
论文题目(英文) Deep-Current Intraseasonal Variability Interpreted as Topographic Rossby Waves and Deep Eddies in the Xisha Islands of the South China Sea  
作者 Shu, Yeqiang;Wang, Jinghong;Xue, Huijie;Huang, Rui Xin;Chen, Ju;Wang, Dongxiao;Wang, Qiang;谢强;Wang, Weiqiang 
发表年度 2022-07-01 
52 
7 
页码 1415-1430 
期刊名称 JOURNAL OF PHYSICAL OCEANOGRAPHY 
摘要   
摘要_英文
 Strong subinertial variability near a seamount at the Xisha Islands in the South China Sea was revealed by mooring observations from January 2017 to January 2018. The intraseasonal deep flows presented two significant frequency bands, with periods of 9-20 and 30-120 days, corresponding to topographic Rossby waves (TRWs) and deep eddies, respectively. The TRW and deep eddy signals explained approximately 60% of the kinetic energy of the deep subinertial currents. The TRWs at the Ma, Mb, and Mc moorings had 297, 262, and 274 m vertical trapping lengths, and similar to 43, 38, and 55 km wavelengths, respectively. Deep eddies were independent from the upper layer, with the largest temperature anomaly being >0.4 degrees C. The generation of the TRWs was induced by mesoscale perturbations in the upper layer. The interaction between the cyclonic-anticyclonic eddy pair and the seamount topography contributed to the generation of deep eddies. Owing to the potential vorticity conservation, the westward-propagating tilted interface across the eddy pair squeezed the deep-water column, thereby giving rise to negative vorticity west of the seamount. The strong front between the eddy pair induced a northward deep flow, thereby generating a strong horizontal velocity shear because of lateral friction and enhanced negative vorticity. Approximately 4 years of observations further confirmed the high occurrence of TRWs and deep eddies. TRWs and deep eddies might be crucial for deep mixing near rough topographies by transferring mesoscale energy to small scales.
 

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