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机构地区:[1]淮海工学院测绘工程学院,江苏连云港222005 [2]中国科学院海洋环流与波动重点实验室,山东青岛266071 [3]南京信息工程大学海洋科学学院,江苏南京210044
出 处:《海洋科学》2013年第9期20-23,共4页Marine Sciences
基 金:中国科学院海洋环流与波动重点实验室开放基金课题(KLOCAW1205);国家自然科学基金(41030855;41025019);淮海工学院引进人才基金(KQ12002)
摘 要:主要利用Lamb模式进行了四个数值敏感实验,研究了背景流、混合层深度对南海东北部内波表面信号强度的影响,并用MASCG指标(表层流梯度绝对值的最大值)进行了量化。研究结果表明:同向背景流能增强内波表面流梯度,逆向背景流则反之。混合层深度对内波表面信号影响很大,深的混合层能弱化内波表面信号强度。内波表面信号的量化依赖于海洋环境条件和内波动力参数,本实验结论将加深对内波遥感观测的理解。The impacts of pycnocline depth and background current on surface signals of underwater internal waves in the northeastern South China Sea (SCS) were studied using four well-designed simulation experiments. The index named maximum absolute value of surface current gradient (MASCG) was used to describe the effect. Model results confirm that the synclastic background current strengthened the horizontal flow gradient of internal waves, while the opposing background current weakened the surface current gradient of internal waves. Pycnocline depth affected dramatically in-ternal wave surface signal. A deeper pycnocline would reduce the internal waves’ surface signal intensity. The quantity of surface signals from oceanic internal waves depends on marine environmental conditions and dynamical characteristics of internal waves. These results may help better understanding of internal waves from remote sensing measurements.
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