物理海洋学
 张坤,男,副研究员,主要从事黑潮的可预报性与目标观测研究,建立了能够处理高维变量的非线性优化系统;揭示了影响其预报准确性的主要因子和物理机制,基于此设计了源区黑潮的最佳观测位置,为提高其预测水平提供了科学支撑。目前,在Journal of Geophysical ResearchJournal of Physical Oceanography等行业高端期刊已发表论文20余篇,主持完成国家自然科学基金面上项目、国家自然科学基金青年科学基金、中国博士后基金等多个科研项目。

一、研究领域 

海洋环流模拟与预测、黑潮的可预报性与目标观测研究                  

二、招生专业及方向

物理海洋学,海洋环流与气候环境效应

三、研究室及联系方式      

中国科学院海洋环流与波动重点实验室

联系电话:0532-82898519 电子邮箱:kzhang@qdio.ac.cn

四、承担的主要科研项目

国家自然科学基金-面上项目,“庆良间水道水交换季节内变异的可预报性与目标观测研究”(项目编号:42376008),2023.01-2028.12,主持

国家自然科学基金-青年项目,“源区黑潮流量季节性变化的可预报性和目标观测研究”,2019.01-2021.12,主持

中国博士后基金项目,“源区黑潮流量季节性下降的适应性观测网构建”,2018.012019.12,主持

横向项目,“三维目标观测系统设计方法”,2019.01-2021.12,主持

国家重点实验室(LASG)开放课题项目,2018.012019.12,主持

国家自然科学基金-重大研究计划,“东海-太平洋间沟弧盆体系对西边界流下层逆流形成及大洋-近海物质能量交换影响研究”,2022.012025.12,参与

国家自然科学基金委员会-面上项目,“热带太平洋海气CO2交换的变异与受控及其对两类ENSO的响应机制”,2023.01-2026.12,参与

国家自然科学基金委员会-重大项目,“海洋环境-生物互作关系及其演化趋势的信息集成与智能分析“,2021.012025.12,参与                         

五、研究成果及奖励        

建立了能够处理高维变量的非线性优化系统,为在业务化模式中开展相关研究工作奠定了技术基础;系统地研究了源区黑潮的可预报性,揭示了影响其预报准确性的主要因子和物理机制;设计了源区黑潮的最佳观测位置,为提高其预测水平提供了科学支撑                          

六、代表性论文及著作

Zhang Kun; Wang Qiang; Yin Baoshu; Yang Dezhou; Yang Lina; Contribution of Deep Vertical Velocity to Deficiency of Sverdrup Transport in the Low-Latitude North Pacific, 2023, 53(11), 2651-2688.

Zhang Kun; Wang Qiang; Yin Baoshu; Decadal sea surface height modes in the low-latitude northwestern Pacific and their contribution to the North Equatorial Current transport variation. Journal of Oceanography, 2022, 78(5): 381-395.

Zhang Kun; Mu Mu; Wang Qiang; Yin Baoshu; Liu Shixuan; CNOP-based adaptive observation network designed for improving upstream Kuroshio transport prediction. Journal of Geophysical Research: Oceans, 2019, 24(6): 4350-4364.

Zhang Kun; Mu Mu; Wang Qiang; Yin Baoshu; Liu Shixuan; Increasingly important role of numerical modeling in oceanic observation design strategy: A review. Science China Earth Sciences, 2020, 63(11): 1678-1690.

Zhang Kun; Mu Mu; Wang Qiang; Identifying the sensitive area in adaptive observation for predicting the upstream Kuroshio transport variation in a 3-D ocean model, Science China Earth Science, 2017, 60(5): 866-875.

Zhang Kun; Wang Qiang; Mu Mu; Liang Peng; Effects of optimal initial errors on predicting the seasonal reduction of the upstream Kuroshio transport, Deep Sea Research Part I: Oceanographic Research Papers, 2016, 116: 220-235.

Zhou L; Mu M; Wang Q; Zhang Kun*Optimally growing initial error for predicting the sudden shift in the Antarctic Circumpolar Current transport and its application to targeted observation, Ocean Dynamics, 2022, 72: 785-800.

Gao Y; Mu M; Zhang Kun*. Impacts of parameter uncertainties on deep chlorophyll maximum simulation revealed by the CNOP-P approach. Journal of Oceanology and Limnology, 2020, 38, 13821393

Mu Mu; Zhang Kun; Wang Qiang: Recent progress in applications of the conditional nonlinear optimal perturbation approach to atmosphere-ocean sciences. Chinese Annals of Mathematics, Series B, 2022,

Zhou L; Wang Q; Mu M; Zhang Kun. Optimal Precursors Triggering Sudden Shifts in the Antarctic Circumpolar Current Transport Through Drake Passage. Journal of Geophysical Research: Oceans, 2021, 126.

Geng; Wang; Mu; Zhang Kun. Predictability and error growth dynamics of the Kuroshio Extension state transition process in an eddy-resolving regional ocean model. Ocean Modelling, 2020, 153.

Yuan; Li; Wang; Zhang Kun; Zhang H; Mu Bin. Optimal precursors of double-gyre regime transitions with an adjoint-free method. Journal of Oceanology and Limnology, 2019, 37(4), 11371153

张坤; 穆穆; 王强; 数值模式在海洋观测设计中的重要作用:回顾与展望. SCIENTIA SINICA Terrae. 2021