代表性研究成果


1)首次将拉格朗日扩散和有效扩散两种定义在理论上完美统一起来,澄清了目前物理海洋界在对这两种定义理解和认识上的误区。 新定义将拉格朗日扩散与分子扩散联系起来,能清楚反映涡旋引起的不可逆混合过程以及给出局地、瞬时、不可逆的扩散分布,克服了其他混合诊断量的不足,为不可逆混合的参数化提供了基础理论依据,对提高当前海洋环流模式的模拟和预报水平具有重要科学意义和应用价值;

2)基于表层漂流浮标长时间系列资料,揭示了南海和印度洋水平扩散系数受主流系环流影响所呈现的各向异性特征,为建立适合南海及印度洋区域的数值模式物理过程参数化方案提供科学依据;

3)对南海北部上升流的动力过程进行系统性研究,揭示了琼西/琼西南和琼东/琼东南上升流的不同产生机制,阐明潮致混合与海洋层结在其中所起的关键作用;

4)发现南海及西太平洋台风(尤其是超强台风)具有向较暖陆面移动以及冷空气入侵会导致台风路径转向的现象和规律,并进一步利用数值试验揭示了这两种过程中下边界层(海表或陆面)与高空环流相互作用的热动力机制,为提高我国台风路径业务预报水平提供新的方法与预报因子;

5)建立适合南海区域的海-气通量参数化方案、风浪混合参数化方案和内潮混合参数化方案,并应用于南海海洋环境预报中,显著提高模式对风暴潮、海浪、层结、环流和海峡水交换的模拟核预报精度;

6)提出“选尺度资料同化方法” (Selective-scale Data Assimilation),并成功应用到区域气候模式的模拟和预报中, 解决区域模式积分过程中大尺度信息失真的问题,显著提高对台风路径和强度及海浪的预报精度;

7)发展针对南海区域的多尺度多变量三维变分海洋资料同化系统,首次实现国产滑翔机温盐观测剖面在预报系统的实时同化,并基于此同化系统形成一套20年南海再分析产品(REDOS),精度优于美国海军同类产品(NCODA);

8)基于准地转位涡理论发展了海表信息向下延拓技术和海洋中尺度涡三维快速植入技术,有效弥补海表以下观测资料稀少的不足,突破当前海洋模式对中尺度涡移动轨迹难以预报的技术瓶颈;

9)发展了普林斯顿海洋模式(Princeton Ocean Model,简称POM)的三维切线性模式(TLM)和共轭伴随模式(Adjoint Model),建立一套基于POM及其共轭伴随模式的海洋资料四维变分同化系统(4DVAR),并成功应用于近海风暴潮的模拟和预报;

10)建成包含先进资料同化方法的海-气-浪耦合的“新一代南海海洋环境实时预报系统”,对南海海洋环境尤其是台风、风暴潮和巨浪进行准确及时的精细化预测预报,并在多个海洋气象部门和国防单位得到应用,为华南地区的防灾减灾、经济建设和国防安全提供重要支持。

近5年(2015-2019)10篇代表性论文


1.Shiqiu Peng, Yuhang Zhu,Zhijin Li, Yineng Li, Qiang Xie, Shijie Liu, Yeteng Luo,Yu Tian & Jiancheng Yu*,2019: Improving the Real-time Marine Forecasting of the Northern South China Sea by Assimilation of Gliderobserved T/S Profiles. Scientific Reports, https://doi.org/10.1038/s41598-019-54241-8.

2.Y.-K Qian, S. Peng*, and C.-X. Liang, 2019: Reconciling Lagrangian diffusivity and effective diffusivity in contour-based coordinates. J. Phys. Oceanogr., doi: 10.1175/JPO-D-1118-0251.1171.

3.Y. Li, S. Peng*, J. Wang, J. Yan, and H. Huang,2018:On the mechanism of the generation and interannual variations of the summer upwellings west and southwest off the Hainan Island. Journal of Geophysical Research: Oceans, 123, 8247–8263. https://doi.org/10.1029/2018JC014226

4.Xiaowei Wang, Zhiyu Liu,and Shiqiu Peng*, 2017: Impact of Tidal Mixing on Water Mass Transformation and Circulation in the South China Sea. Journal of Physical Oceanography, 47(2), 419-432-124.

5.Lei Liu, Shiqiu Peng*, and Rui Xin Huang, 2017: Reconstruction of ocean's interior from observed sea surface information. Journal of Geophysical Research, 122, 1042-1056, DOI: 10.1002/2016JC011927.

6.Shiqiu Peng*, Xuezhi Zeng, and Zhijin Li, 2016: A Three-Dimensional Variational Data Assimilation System for the South China Sea: Preliminary Results from Observing System Simulation Experiments. Ocean Dynamic, 66(5), 737-750.

7.Xiaowei Wang, Shiqiu Peng*, Zhiyu Liu, Rui Xin Huang, Yu-Kun Qian and Yineng Li, 2016: Tidal Mixing in the South China Sea: An Internal-Tide-Energetics-Based Estimate. Journal of Physical Oceanography, 46(1), 107-124.

8.Shiqiu Peng* and Yineng Li, 2015: A parabolic model of drag coefficient for storm surge simulation in the South China Sea. Scientific Reports. DOI: 10.1038/srep15496.

9.Shiqiu Peng*,Yu-kun Qian, Rick Lumpkin, Ping Li, Dongxiao Wang and Yan Du, 2015:Characteristics of the Near-Surface Currents in the Indian Ocean as Deduced from Satellite-Tracked Surface Drifters. Part II: Lagrangian Statistics. Journal of Physical Oceanography,45(2):459-477.

10.Shiqiu Peng*, Yineng Li, Xiangquan Gu, Shumin Chen, Dongxiao Wang, Hui Wang, Shuwen Zhang, Weihua Lv, Chunzai Wang, Bei Liu, Duanling Liu, Zhijuan Lai, Wenfeng Lai, Shengan WANG, Yerong Feng, Junfeng Zhang, 2015: A real-time regional forecasting system in the South China Sea and its performance in the track forecasts of tropical cyclones during 2011-2013. Weather and Forecast, 30,471-485.