The South China Sea (SCS) is dominated by the diurnal internal tide, and internal tide induced mixing plays a very important role in driving the deep ocean circulation. Recently, fine-scale observations found that the enhanced mixing in the SCS basin is of comparable magnitude to that in the Luzon Strait. However, most of the previous research of internal tide induced mixing were concentrated on the north SCS, the far field dissipation mechanism of the long range propagating internal tide is still unclear. The proposed research focuses on the nonlinear fission of diurnal internal tide and associated mixing in the middle of SCS basin. Based on the high resolution numerical model, here we propose to investigate the spacial structure of the propagating internal tide and its variation, to analysis the down-scale energy transmission of internal tide int he vicinity of the critical latitude, to explore the potential importance of Parametric Subharmonic Instability (PSI) as a dissipation mechanism of internal tide, and to quantitatively estimate the relative contribution in local mixing of both the near-field and far-field generated internal tide. The research will map the spatial distribution of PSI induced mixing by diurnal internal tide and deepen our understanding of the SCS mixing progress.
南海是全日内潮占优势的海域,内潮致混合是南海深层环流的重要驱动力。近年来,国内外很多学者对南海内潮进行了广泛的研究。最近的观测表明南海中部海盆是与吕宋海峡量级相当的强混合区,但以往的研究大多集中在南海北部,对于内潮跨海盆尺度的能量传输及其非局地耗散引起的混合的研究仍然十分缺乏。本项目拟针对全日内潮在南海长距离传播过程中的非线性裂变(Parametric Subharmonic Instability,PSI)及其导致的混合展开深入研究。基于高分辨率数值模拟结果,结合卫星遥感和现场观测资料,研究内潮波束在跨海盆传播过程中的空间结构特征与变化规律;分析临界纬度附近内潮能量的降尺度传递过程;评估PSI机制在内潮非局地耗散过程中的有效性;并定量估算非局地和局地全日内潮对南海中部混合的贡献。通过对上述问题的系统研究,阐明南海全日内潮PSI致混合的强度以及空间分布特征,以加深我们对南海混合过程的理解。
吕宋海峡内潮是南海混合的重要能量来源,但目前其非局地耗散机制仍不清楚。南海地理位置独特,吕宋海峡低模态K1内潮波束在南海中部穿越其临界纬度(14.48ºN),因此,参数化次谐波不稳定机制(Parametric Subharmonic Intability,PSI)是吕宋海峡内潮在南海长距离传播后非局地耗散的潜在有效机制。本项目基于高分辨率海洋数值模型MITgcm开展了吕宋海峡低模态全日内潮跨海盆传播过程与演变研究,分析了临界纬度附近全日内潮能量在物理空间和波谱空间的再分配过程,定量评估了PSI机制在南海全日内潮非局地耗散过程中的有效性,并给出了考虑PSI的南海全日内潮致混合三维分布特征。本项目的成果有助于我们进一步了解南海内潮的能量串级过程,加深我们对南海内潮非局地耗散机制的认知。
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数据更新时间:2023-05-31
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