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于亮 Liang Yu

气候动力学博士 Ph.D. in Climate Dynamics

个人总结 Profile

于亮，博士，大连海事大学航海学院讲师。2019 年获美国乔治梅森大学气候动力学博士学位，长期从事 ENSO 年际至年代际变率机理及其对全球气候影响的研究。精通气候数值模式（CESM）的运行与调试，熟练运用 Fortran、NCL、GrADS 等工具开展数据处理、统计分析与可视化。

工作之余，喜欢研究修理各种东西，偶尔在 B 站 分享相关DIY视频。 Dr. Liang Yu is a Lecturer at the School of Navigation, Dalian Maritime University. He received his Ph.D. in Climate Dynamics from George Mason University in 2019. His research focuses on the mechanisms of ENSO variability on interannual-to-decadal timescales and its impacts on global climate. He is experienced in running and debugging the CESM climate model, and proficient in data processing, statistical analysis, and visualization using Fortran, NCL, and GrADS.

Outside of work, he enjoys tinkering with things, and occasionally shares videos of his DIY projects on Bilibili.

工作经历 Experience

讲师 Lecturer 2020 – 至今Present
大连海事大学 · 航海学院 · 气象教研室 Department of Meteorology, School of Navigation, Dalian Maritime University
从事 ENSO 年际至年代际变率机理及其对全球气候影响的研究，同时承担专业核心课《航海气象学与海洋学》的教学工作。 Conducts research on the mechanisms of ENSO variability on interannual-to-decadal timescales and its impacts on global climate, while teaching maritime meteorology courses.

教育背景 Education

气候动力学 · 博士 Ph.D. in Climate Dynamics 2013 – 2019
美国乔治梅森大学 George Mason University, USA
气象学 · 硕士 M.S. in Meteorology 2010 – 2013
中国科学院海洋研究所 Institute of Oceanology, Chinese Academy of Sciences
大气科学 · 学士 B.S. in Atmospheric Science 2006 – 2010
南京大学 Nanjing University, China

科研经历 Research Experience

研究助理 Research Assistant 2013 – 2019
美国乔治梅森大学（弗吉尼亚） George Mason University, Virginia, USA
  • 多年在大型高性能计算集群上运行与调试气候模式的经验，熟悉美国国家大气研究中心（NCAR）Yellowstone 超算平台。
  • 独立开发 CESM1.1.1 模式自定义数据读取系统，支持按需灵活读取指定数据，显著提升模式实验与分析效率。
  • 调试 CESM 模式，成功实现大西洋经圈翻转环流（AMOC）长达 600 年的数值模拟。
  • 使用 Fortran 与 NCL 开展相关性分析、经验正交分解（EOF）等统计学分析，并借助 NCL 与 GrADS 完成资料可视化。
  • Years of experience running and debugging climate models on large high-performance computing clusters; familiar with the NCAR Yellowstone supercomputer.
  • Independently developed a custom data-reading system for the CESM1.1.1 model, enabling flexible ingestion of user-defined data and accelerating model experiments and analysis.
  • Debugged the CESM model and successfully simulated 600 years of Atlantic Meridional Overturning Circulation (AMOC) variability.
  • Performed statistical analyses (e.g., correlation analysis and Empirical Orthogonal Function decomposition) with Fortran and NCL, and created visualizations with NCL and GrADS.
研究助理 Research Assistant 2010 – 2013
中国科学院海洋研究所（山东青岛） Institute of Oceanology, CAS (Qingdao, China)
  • 发展了洛伦兹方程的伴随模式，系统研究其方程组误差的发展演变特性。
  • 采用条件非线性最优扰动（CNOP）方法，确定了 Zebiak–Cane（ZC）模式中 ENSO 预报初始误差与参数误差的最优组合。
  • 证实初始误差在 ENSO 春季预报障碍（SPB）的形成中起决定性作用。
  • Developed the adjoint model of the Lorenz equations to investigate the error evolution characteristics of the system.
  • Applied the Conditional Nonlinear Optimal Perturbation (CNOP) approach to identify the optimal combination of initial and parameter errors in ENSO forecasts within the Zebiak–Cane (ZC) model.
  • Demonstrated that initial errors play a decisive role in the formation of the ENSO Spring Predictability Barrier (SPB).

专业技能 Skills

编程语言 Programming Languages
Fortran C Matlab R NCL GrADS Java
平台与工具 Platform & Tools
Linux CESM NCO C-Shell HPC

获奖经历 Awards

发表论文 Publications

  1. Liang Yu, Barry Klinger. Response of upper and deep Atlantic Ocean to surface forcings on multidecadal time scales in CESM. Climate（Accepted in 2026.5） Liang Yu, Barry Klinger. Response of upper and deep Atlantic Ocean to surface forcings on multidecadal time scales in CESM. Climate (Accepted in May 2026)
  2. P. A. Dirmeyer, Liang Yu, S. Amini, A. D. Crowell, A. Elders, J. Wu. Projections of the shifting envelope of water cycle variability. Climate Change, 2016. P. A. Dirmeyer, Liang Yu, S. Amini, A. D. Crowell, A. Elders, J. Wu. Projections of the shifting envelope of water cycle variability. Climate Change, 2016.
  3. 于亮. Zebiak–Cane 模式中条件非线性最优扰动对 ENSO 春季预报障碍的影响. 海洋科学, 2015. Liang Yu. Impacts of conditional nonlinear optimal perturbation on the ENSO Spring Predictability Barrier in the Zebiak–Cane model. Marine Sciences, 2015.
  4. Liang Yu, Mu Mu, Yanshan Yu. Role of parameter errors in the spring predictability barrier for ENSO events in the Zebiak–Cane model. Advances in Atmospheric Sciences, 2014. Liang Yu, Mu Mu, Yanshan Yu. Role of parameter errors in the spring predictability barrier for ENSO events in the Zebiak–Cane model. Advances in Atmospheric Sciences, 2014.
© 2026 于亮 · 大连海事大学 © 2026 Liang Yu · Dalian Maritime University