段晚锁个人主页

段晚锁
中国科学院大气物理研究所LASG
电话：010-82995302
传真：010-82995172
Email:duanws@lasg.iap.ac.cn

兴趣链接

* 中国科学院大气物理研究所
 * 大气科学和地球流体力学数值模拟国家重点实验室

个人简介

段晚锁，中国科学院大气物理研究所，研究员（二级；中科院特聘研究员；国科大岗位教授），博士生导师，全国百篇优秀博士论文，及国家杰出青年科学基金获得者。兼任SCI杂志"Nonlinear Processes in Geophysics" 和 "Advance in Atmospheric Sciences" 编委、AIMS Geosciences杂志编委、核心期刊《大气科学》常务编委，以及国际动力气象学委员会（ICDM）、世界气候研究计划（WCRP）中国委员会、国际气象和大气科学协会（IAMAS）中国委员会委员等。目前的研究方向为：海气相互作用，以及台风、厄尔尼诺、印度洋偶极子等高影响天气、气候事件和海洋中尺度涡的可预报性、目标观测、资料同化和集合预报等。

学术论文

On the use of near-neutral backward Lyapunov vectors to get reliable ensemble forecasts in coupled ocean-atmosphere systems.Stéphane Vannitsem, Wansuo Duan, Climate Dynamics, 2020. doi: 10.1007/s00382-020-05313-3[PDF]
Improving forecasts of El Niño diversity: a nonlinear forcing singular vector approach. Tao Linjiang, Duan Wansuo, and Stephane Vannitsem, Climate Dynamics. 2020. doi: 10.1007/s00382-020-05292-5[PDF]
Sensitivity on tendency perturbations of tropical cyclone short-range intensity forecasts generated by WRF. Qin Xiaohao, Duan Wansuo, and Xu Hui, Advances in Atmospheric Sciences, 2020. 37, 291-306.[PDF]
Errors in current velocity in the low-latitude north Pacific: results from the regional ocean modeling system. Wen Xixi, Duan Wansuo, Advances in Atmospheric Sciences, 2019, 36, 397-416.[PDF]
近海台风立体协同观测科学试验, 雷小途, 张雪芬, 段晚锁, 李泓, 高志球, 钱传海, 赵兵科, 和汤杰, 地球科学进展: 2019, 34 (7), 671-678.[PDF]
Exploring sensitive area in the tropical Indian Ocean for El Nino predictions: implication for targeted observation. Zhou Qian, Duan Wansuo, Hu Junya. Journal of Oceanology and Limnology. 2019. doi: 10.1007/s00343-019-9062-4[PDF]
Ensemble Forecasts of Tropical Cyclone Track with orthogonal Conditional Nonlinear Optimal Perturbations. Huo Zhenhua, Duan Wansuo, Feifan Zhou, Advances in Atmospheric Sciences, 2019. 36(2), 231-247.[PDF]
The Initial Condition Errors Occurring in the Indian Ocean Temperature That Cause “Spring Predictability Barrier” for El Niño in the Pacific Ocean. Qian Zhou, Mu Mu, and Wansuo Duan. JGR-Ocean, 2019 doi: 10.1029/2018JC014403[PDF]
Season-dependent predictability and error growth dynamics for La Niña predictions. Hu Junya, Duan Wansuo, and Zhou Qian, Climate Dynamics. 2019, doi: 10.1007/s00382-019-04631-5[PDF]
Indian Ocean Dipole-related predictability barriers induced by initial errors in the tropical Indian Ocean in a CGCM, Feng Rong, and Duan Wansuo, Advances in Atmospheric Sciences. 2019. 36, 658-668. doi: 10.1007/s00376-019-8224-9.[PDF]
数值天气预报、气候预测的集合预报方法：思考与展望。段晚锁，汪叶，霍振华，周菲凡。气候与环境研究， 2019。24（3），396-406。[PDF]
Season-dependent predictability barrier for two types of El Niño-Southern Oscillation events revealed by an approach to data analysis for predictability. Hou Meiyi, Wansuo Duan, Xiefei Zhi. Climate Dynamics. 2019. doi: 10.1007/s00382-019-04888-w. [PDF]
初始扰动振幅和集合样本数对CNOPs集合预报的影响，汪叶, 段晚锁，大气科学，2019，43(4)，919-933。[PDF]
Using a nonlinear forcing singular vector approach to reduce model error effects in ENSO forecasting. Tao Lingjiang, and Wansuo, Duan, Weather and Forecasting. 2019. 1321-1342. DOI: 10.1175/WAF-D-19-0050.1[PDF]
Towards optimal observational array for dealing with challenges of El Niño-Southern Oscillation predictions due to diversities of El Niño. Duan Wansuo, Li Xuquan, Tian Ben. Climate Dynamics, 2018. doi:10.1007/s00382-018-4082-x.[PDF]
Impact of SST anomaly events over the Kuroshio-Oyashio Extension on the "summer prediction barrier". Wu Yujie, Wansuo Duan. Advances in Atmospheric Sciences, 2018. 35, 397-409.[PDF]
Predictability of El Niño-Southern Oscillation Events. Duan Wansuo, Mu Mu, Oxford Research Encyclopedia of Climate Science, 2018. doi:10.1093/acrefore/9780190228620.013.80.[PDF]
"Summer Predictability Barrier" of Indian Ocean Dipole Events and Corresponding Error Growth Dynamics, Liu Da, Duan Wansuo, Feng Rong, Tang Youmin, JGR: Ocean, 2018. 123, doi: 10.1029/2017JC013739[PDF]
季风与ENSO的选择性相互作用：年循环和春季预报障碍的影响。杨崧，邓开强，段晚锁，大气科学，2018，42(3), 570-589 [PDF]
粒子滤波同化在厄尔尼诺-南方涛动目标观测中的应用。段晚锁，封凡，侯美夷，大气科学，2018，42(3), 677-695[PDF]
Asymmetry of the predictability limit of the warm ENSO phase. Hou Zhaolu, Jianping Li, Ruiqiang Ding, Christina Karamperidou, Wansuo Duan, Ting Liu, and Jie Feng, 2018. Geophysical Research Letters. 45. 10.1029/2018GL077880. [PDF]
Investigating the initial errors that cause predictability barriers for IOD events using CMIP5 model outputs. Feng Rong and Wansuo Duan, Advances in Atmospheric Sciences, 2018. 35(10), 1305-1320.[PDF]
Possible sources of forecast errors generated by the global/regional assimilation and prediction system for landfalling tropical cyclones. Part II: model uncertainty. Zhou Feifan, Wansuo Duan, He Zhang, Munehiko Yamaguchi, Adv. Atmos. Sci., 2018. 35, 1277-1290. [PDF]
The application of the orthogonal conditional nonlinear optimal perturbations method to typhoon track ensemble forecasts. Huo Zhenhua and Wansuo Duan, SCIENCE CHINA Earth Sciences. 2018.10.1007/s11430-018-9248-9[PDF]
北京地区一次空气重污染过程的目标观测分析[J]。刘娜，段晚锁，王自发，唐晓，周菲凡。气候与环境研究。 2018, 23，619-632 [PDF]
Progress in ENSO prediction and predictability study. Tang Youmin, Ronghua Zhang, Ting Liu, Wansuo Duan, et al. National Science Review, 2018, 5(6), 840-857. doi:10.1093/nsr/nwy105.[PDF]
The role of initial signals in the tropical Pacific Ocean in predictions of negative Indian Ocean Dipole events. Feng Rong and Wansuo Duan, SCIENCE CHINA Earth Sciences, 2018. 61. doi:10.1007/s11430-018-9296-2[PDF]
Relationship between optimal precursors for Indian Ocean Dipole events and optimally growing initial errors in its prediction. Mu, Mu, Rong Feng, and Wansuo Duan. Journal of Geophysical Research: Oceans, 2017, 122, doi:10.1002/2016JC012527. [PDF]
Reducing the prediction uncertainties of high-impact weather and climate events: an overview of studies at LASG. Duan Wansuo and Rong Feng. Journal of Meteorological Research. 2017. 31, 224-235, doi: 10.1007/s13351-016-6099-6.[PDF]
Nonlinearity modulating intensities and spatial structures of Central Pacific- and Eastern Pacific-El Niño events, Duan Wansuo, Chaoming Huang, Hui Xui, Adv. Atmos. Sci., 2017. 34,737-756.[PDF]

Questions, comments, suggestions? E-Mail me, please!
duanws@lasg.iap.ac.cn