基本信息
段晚锁  男  博导  中国科学院大气物理研究所
电子邮件: duanws@lasg.iap.ac.cn
通信地址: 北京9804信箱
邮政编码: 100029

研究方向

海气相互作用,天气、气候可预报性,集合预报,目标观测等

招生信息

欢迎有志于从事天气、气候动力学及可预报性研究的青年教师及学生(本科生及硕士研究生)报考

招生专业
070601-气象学
070620-地球流体力学
070701-物理海洋学
招生方向
海气相互作用
天气、气候可预报性; 集合预报,资料同化和目标观测

教育背景

2000-09--2003-07   中科院大气物理研究所   (气象学)研究生/博士学位
1997-09--2000-07   昆明理工大学   (应用数学专业)研究生/硕士
1991-09--1995-07   山西大学   (基础数学)本科/学士

工作经历

2019-08~2019-08,Royal Meteorological Institute of Belgium, 高访
2017-07~2017-08,University of Northern British Columnbia, Prince Geoger, Canada, 高级访问学者
2016-01~现在, 中国科学院, 特聘研究员
2015-01~现在, 中国科学院大学, 岗位教授
2014-03~2014-04,澳大利亚CSRIO, 高级访问学者
2010-01~现在, 中科院大气物理研究所, 研究员
2006-11~2010-01,中科院大气物理研究所, 副研究员
2003-07~2006-11,中科院大气物理研究所, 助理研究员


教授课程

地球流体动力学
非线性大气和海洋动力学

奖励与任职

获奖与荣誉

(1)2020年获“国务院政府特殊津贴”;

(2)2019年获中科院朱李月华优秀教师奖;

(3)2016年获得中科院青年创新促进会优秀会员;

(4)2015年被评为中科院大气物理研究所“2015年度先进工作者”;

(5)2015年获得“国家杰出青年科学基金”;

(6)2011年入选“中国科学院青年人才创新促进会”会员;

(7)2009年获“中国科学院卢嘉锡青年人才奖”;

(8)2009年被评为中科院大气物理研究所“2009年度先进工作者”;

(9)2006年获教育部、国务院学位委员会“全国优秀博士论文”奖;

(10)2006年获中国气象学会“全国优秀青年气象科技工作者奖”;

(11)2005年获“中国科学院优秀博士论文奖”,等等。


国际任职

(1)Journal of Tropical Meteorology 编委,2022.7-2025.12

(2)《干旱气象》杂志编委,2021.9-今

(3)Journal of Marine Science and Engineering编委, 2021.2-今;

(4)国际气象与大气科学协会(IAMAS)中国委员会,2020.7-今;

(5)Nonlinear Processes in Geophysics, editor,2017.10-今;

(6)第七届CNC-WCRP委员,2016-今;

(7)宁波大学非线性海气灾害系统协同创新中心学术委员会委员,2014-2019;

(8)“10000个科学难题”海洋科学编辑委员会委员,2015.12-2017.1;

(9)国际动力气象学委员会(IAMAS-ICDM)委员,2013.8-今;

(10) 中国气象学会动力气象学委员会委员,2011-今;

(11)“Advance in Atmospheric Sciences”杂志associate editor,2010-2012;

(12)“Advance in Atmospheric Sciences”杂志editor,2013-今;

(13)“Advances in Meteorology” 杂志Guest editor,2011-2012;

(14)《大气科学》常务编委,2010-今;

(15)国务院学位委员会大气科学学科评议组学术秘书,2009-今



发表论文

(1)Effects of dropsonde data in field campaigns on forecasts of tropical cyclones over the western North Pacific in 2020 and role of CNOP sensitivity. Advances in Atmospheric Sciences, 2022.

(2)A novel enseble forecasting approach for dealing with combined effect of initial errors and model errors.Mon. Wea. Rev., 2022

(3)Evaluation and Projections of Precipitation Extremes using a Spatial Extremes Framework. Weather and Climate Extremes. 2022

(4)Toward target observations of the meteorological initial state for improving the PM2.5 forecast of a heavy haze event that occurred in the Beijing-Tianjin-Hebei region.  Atmospheric Chemistry and Physics, 2022

(5)A new approach to data assimilation for numerical weather forecasting and climate prediction.  Journal of Applied Analysis and Computation. 2022

(6)非线性最优扰动方法在热带气旋目标观测研究和外场试验中的应用。地球科学进展,2022

(7)Toward an optimal observational array for improving two flavors of El Niño predictions in the whole Pacific.  Climate Dynamics, 2022.

(8)The different relationships between ENSO spring Persistence Barrierand Predictability Barrier.  Journal of Climate, 2022.

(9)The most sensitive initial error of sea surface height anomaly forecasts and its implication for target observations of mesoscale eddies. J. Physical Oceanography. 2022.

(10)台风强度模拟的海温目标观测研究,大气科学,2022. 通讯作者

(11)Seasonally Alternate Roles of the North Pacific Oscillation and the South Pacific Oscillation in Tropical Pacific Zonal Wind and ENSO.J. Climate, 2021

(12)A precursory signal of the Central Pacific El Niño event: Eastern Pacific cooling mode. J. Climate. 2021

(13)Model errors of an intermediate model and their effects on realistic predictions of El Niño diversity.JGR-Atmosphere, 2021. 

(14)Using Conditional Nonlinear Optimal Perturbation to Generate Initial Perturbations in ENSO Ensemble Forecasts.  Weather and Forecasting. 2021. 通讯作者

(15)How does El Nino affect predictability barrier of its accompanied positive Indian Ocean Dipole event? J. Marine Sciences and Engineering. 2021. 通讯作者

(16)The most sensitive initial error modes modulating intensities of CP- and EP- El Niño events. Dynamics of Atmospheres and Oceans, 2021, 通讯作者

(17)Interdecadal change in the relationship between boreal winter North Pacific Oscillation and Eastern Australian rainfall in the following autumn.  Climate Dynamics. 2021. 

(18)The Initial Errors in the Tropical Indian Ocean that Can Induce a Significant “Spring Predictability Barrier” for La Niña Events and Their Implication for Targeted Observations. Advances in Atmospheric Sciences, 2021. 

(19)On the sensitive areas for targeted observations in ENSO forecasting,  AOSL, 2021.  通讯作者

(20)Typhoon intensity forecasting based on LSTM using the rolling forecast method,  Algorithms,2021

(21)Optimally growing initial errors of El Nino events in the CESM, 2021, Climate Dynamics

(22)Which features of the SST forcing error are most likely to disturb the simulation of tropical cyclone intensity?  Adavnces in Atmospheric Sciences, 2021. 通讯作者

(23)Forecast uncertainty of rapid intensification of typhoon Dujuan (201521) induced by uncertainty in the boundary layer.  Atmosphere, 2020. 通讯作者

(24)Model forecast error correction based on the Local Dynamical Analog method: an1example application to the ENSO forecast by an Intermediate Coupled Model. Geophysical Research Letters. 2020.

(25)Predictable patterns of wintertime surface air temperature in Northern Hemisphere and their predictability sources in SEAS5, Journal of Climate, 2020

(26)Improving forecasts of El Niño diversity: a nonlinear forcing singular vector approach.  Climate Dynamics, 2020. 通讯作者

(27)On the use of near-neutral backward Lyapunov vectors to get reliable ensemble forecasts in coupled ocean-atmosphere systems. Climate Dynamics, 2020

(28) Sensitivity on tendency perturbations of tropical cyclone short-range intensity forecasts generated by WRF. Advances in Atmospheric Sciences, 2020

(29)Errors in current velocity in the low-latitude north Pacific: results from the regional ocean modeling system. Advances in Atmospheric Sciences, 2019.通讯作者

(30)近海台风立体协同观测科学试验。地球科学进展,2019。

(31)Exploring sensitive area in the tropical Indian Ocean for the El Nino predictions: an implication for targeted observation. Journal of Oceanology and Limnology, 2019. 通讯作者

(32)Using a nonlinear forcing singular vector approach to reduce model error effects in ENSO forecasting. Weather and Forecasting, 2019. 通讯作者

(33)始扰动振幅和集合样本数对CNOPs集合预报的影响。大气科学,2019,已接收。通讯作者

(34)Season-dependent predictability barrier for two types of El Niño-Southern Oscillation events revealed by an approach to data analysis for predictability. Climate Dynamics, 2019. 通讯作者

(35)数值天气预报、气候预测的集合预报方法:思考与展望。气候与环境研究,2019。第一作者

(36)Indian Ocean Dipole-related predictability barriers induced by initial errors in the tropical Indian Ocean in a CGCM. Advances in Atmospheric Sciences, 2019. 通讯作者

(37)Season-dependent predictability and error growth dynamics for La Niña predictions. Climate Dynamics, 2019. 通讯作者

(38)The Initial Condition Errors Occurring in the Indian Ocean Temperature That Cause “Spring Predictability Barrier” for El Niño in the Pacific Ocean. JGR-Ocean, 2019. 通讯作者

(39)Ensemble forecasts of tropical cyclone track with orthogonal conditional nonlinear optimal perturbations.  Advances in Atmospheric Sciences, 2019. 通讯作者

(40)The role of initial signals in the tropical Pacific Ocean in predictions of negative Indian Ocean Dipole events. SCIENCE CHINA Earth Sciences. 2018. 通讯作者

(41) Progress in ENSO prediction and predictability study. National Science Review. 2018.

(42)Asymmetry of the predictability limit of the warm ENSO phase. Geophysical Research Letters. 2018.

(43)The application of the orthogonal conditional nonlinear optimal perturbations method to typhoon track ensemble forecasts. SCIENCE CHINA Earth Sciences. 2018. 通讯作者

(44)Impact of SST anomaly events over the Kuroshio-Oyashio Extension on the "summer prediction barrier".Advances in Atmospheric Sciences, 2018.

(45)北京地区一次空气重污染过程的目标观测分析[J]. 气候与环境研究. 2018. 通讯作者

(46)"Summer Predictability Barrier" of Indian Ocean Dipole Events and Corresponding Error Growth Dynamics. JGR-Ocean, 2018. 通讯作者 

(47)Possible sources of forecast errors generated by the global/regional assimilation and prediction system for landfalling tropical cyclones. Part II: model uncertainty. Adv. Atmos. Sci., 2018.

(48)Investigating the initial errors that cause predictability barriers for IOD events using CMIP5 model outputs. Advances in Atmospheric Sciences, 2018. 通讯作者 

(49) Towards optimal observational array for dealing with challenges of El Niño-Southern Oscillation predictions due to diversities of El Niño. Climate Dynamics, 2018.第一作者

(50)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。大气科学,2018

(51)粒子滤波同化在厄尔尼诺-南方涛动目标观测中的应用。大气科学,2018. 第一作者

(52)Predictability of El Niño-Southern Oscillation Events.Oxford Research Encyclopedia of Climate Science, 2018. 第一作者

(53)The application of nonlinear local Lyapynov vectors to the Zebiak-Cane model and their performance in ensemble prediction. Clim Dyn. 2017.

(54)耦合模式中北太平洋和北大西洋海表面温度年代际可预报性和预报技巧的季节依赖性,地球科学进展,2017.

(55)The predictability of atmospheric and oceanic motions: Retrospect and prospects.Science China: Earth Sciencess, 2017. 通讯作者

(56)On the "spring predictability barrier" for strong El Nino events as derived from an intermediate coupled model ensemble prediction system. SCIENCE CHINA Earth Sciences, 2017. 通讯作者

(57)Nonlinearity Modulating Intensities and Spatial Structures of Central Pacific- and Eastern Pacific-El Niño Events. Adv. Atmos. Sci., 2017.第一作者 

(58)Relationship between optimal precursors for Indian Ocean Dipole events and optimally growing initial errors in its prediction. Journal of Geophysical Research: Oceans, 2017.

(59)Reducing the prediction uncertainties of high-impact weather and climate events: an overview of studies at LASG. Journal of Meteorological Research. 2017.第一作者

(60)Numerical Analysis of the Mixed 4th-Order Runge-Kutta Scheme of Conditional Nonlinear Optimal Perturbation Approach for the El Nino-Southern Oscillation Model, Adv. Appl. Math. Mech., 2016.

(61)The role of nonlinear forcing singular vector tendency error in causing the "spring predictability barrier" for ENSO. Journal of Meteorological Research, 2016.第一作者

(62)IOD-related optimal initial errors and optimal precursors for IOD predictions from reanalysis data.  SCIENCE CHINA Earth Sciences. 2016,通讯作者

(63)Seasonal predictability of sea surface temperature anomalies over the Kuroshio-Oyashio Extension: low in summer and high in winter, JGR-Ocean, 2016,通讯作者

(64)Time-scale Decomposed Threshold Regression Downscaling Approach to Forecasting South China Early Summer Rainfall, Advances in Atmospheric Sciences, 2016,通讯作者

(65)Relationship between optimal precursory disturbances and optimally growing initial errors associated with ENSO events: Implications to target observations for ENSO prediction. Journal of Geophysical Research - Oceans, 2016.通讯作者

(66)Estimating observing locations for advancing beyond the winter predictability barrier of Indian Ocean dipole event predictions, Climate Dynamics,2016. 通讯作者

(67)Comparison of constant and time-variant optimal forcing approaches in El Niño simulations by using the Zebiak-Cane model.  Adv. Atmos. Sci., 2016. 通讯作者

(68)An approach to generating mutually independent initial perturbations for ensemble forecasts: orthogonal conditional nonlinear optimal perturbations. J. Atmos. Sci., 2016. 第一作者

(69)Application of Conditional Nonlinear Optimal Perturbation to Targeted Observation Studies of the Atmosphere and Ocean,  J. Meteor. Res,. 2015

(70)关于线性奇异向量和条件非线性最优扰动差别的一个注记。气候与环境研究,2015,通讯作者

(71)The influence of boreal winter extratropical North Pacific Oscillation on Australian spring rainfall, Clim Dyn, 2015, 通讯作者 

(72) Dynamics of nonlinear error growth and the "spring predictability barrier" for El Nino predictions. Duan Wansuo, Mu Mu, Chapter 5 in Climate Change edited by Chin-Pei Chang, Michael Ghil, Mojib Latif, and John M. Wallace. World Scientific Series on Asian-Pacific Weather and Climate, 2015.

(73)Comparison of the initial errors most likely to cause a spring predictability barrier for two types of El Nino event. Clim Dyn, 2015, 通讯作者

(74) Interannual Relationship between the Winter Aleutian Low and Rainfall in the Following Summer in South China, Atmos. Oceanic Sci. Lett, 2015,通讯作者

(75) The initial errors that induce a significant “spring predictability barrier” for El Nino events and their implications for target observations:results from an earth system model,Clim Dyn, 2015,第一作者

(76) Target observations for improving initialization of high-impact ocean-atmospheric environmental events forecasting, National Science Review,2015, 通讯作者

(77) The “winter predictability barrier” for IOD events and its error growth dynamics: results from a fully coupled GCM, Journal of Geophysical Research: Oceans, 2014, 通讯作者

(78) Influence of Positive/Negative Indian Ocean Dipole on Pacific ENSO through Indonesian Throughflow: results from Sensitivity Experiments, Adv. Atmos. Sci., 2014, 通讯作者

(79) Revealing the most disturbing tendency error of Zebiak-Cane model associated with El Nino predictions by nonlinear forcing singular vector approach,Climate Dynamics,2014,第1作者 

(80) Season-dependent predictability and error growth dynamics of Pacific Decadal Oscillation-related sea surface temperature anomalies,Climate Dynamics,2014,第1作者 

(81) Study on the “winter persistence barrier” of Indian Ocean dipole events using observation data and CMIP5 model outputs,Theoretical and Applied Climatology,2014,通讯作者 

(82) A SVD-based ensemble projection algorithm for calculating conditional nonlinear optimal perturbation, SCIENCE CHINA: Earth Sciences,2014,第2作者

(83)  Using CMIP5 model outputs to investigate the initial errors that cause the “spring predictability barrier” for El Niño events, SCIENCE CHINA: Earth Sciences, 2014,通讯作者 

(83)  ENSO预测的目标观测敏感区在热带太平洋海温的多模式集合预报中的应用,大气科学,2014,通讯作者 

(84) Time-dependent nonlinear forcing singular vector-type tendency error of the Zebiak-Cane model, Atmos. Oceanic Sci. Lett., 2014,通讯作者 

(85)The combined effect of initial error and model error on ENSO prediction uncertainty generated by the Zebiak-Cane model, Atmos. Oceanic Sci. Lett., 2014,通讯作者 

(86) The spatial patterns of initial errors related to the “winter predictability barrier” of the Indian Ocean dipole, Atmos. Oceanic Sci. Lett., 2014,通讯作者 

(87) Conditions under which CNOP Sensitivity Is Valid for Tropical Cyclone Adaptive Observations,Quarterly J. RMS,2013,通讯作者 

(88) 条件非线性最优扰动方法在可预报性研究中的应用,大气科学,2013,第2作者 

(89) 数值天气预报和气候预测可预报性研究的若干动力学方法,气候与环境研究,2013,第1作者 

(90) Climate Variability and Predictability at Various Time Scales,Advances in Meteorology,2013,第3作者 

(91) Seasonal modulations of different impacts of two types of ENSO events on tropical cyclone activity in the western North Pacific,Climate Dynamics,2013,第4作者 

(92) Modulation of PDO on the predictability of the inter-annual variability of early summer rainfall over South China,JGR-Atmosphere,2013,第1作者 

(93) Simulations of two types of El Nino events by an optimal forcing vector approach,Climate Dynamics,2013,第1作者 

(94) The role of nonlinearities associated with air-sea coupling processes in El Nino’s peak-phase locking,Sciences in China (D),2013,第1作者 

(95) Behaviors of nonlinearities modulating El Nino events induced by optimal precursory disturbance,Climate Dynamics,2013,第1作者 

(96) The role of constant optimal forcing in correcting forecast model,Sciences in China (D),2013,通讯作者 

(97) Nonlinear forcing singular vector of a two-dimensional quasi-geostrophic model,Tellus-A,2013,第1作者 

(98) Does model parameter error cause a significant spring predictability barrier for El Nino events in the Zebiak-Cane model,J. Climate,2012,通讯作者 

(99)Contribution of the location and spatial pattern of initial error to uncertainties in El Nino predictions,JGR-Ocean,2012,第3作者 

(100) The spring predictability barrier for ENSO predictions and its possible mechanism: results from a fully coupled model,Inter. J. Climatology,2012,第1作者 

(101) The amplitude-duration relation of the observed El Nino events,Atmos. Oceano. Sci. Lett.,2012,通讯作者 

(102) 四个耦合模式ENSO后报试验的“春季预报障碍”,气象学报,2012,第3作者 

(103)Progresses in the studies of nonlinear atmospheric dynamics and predictability for weather and climate in China (2007-2010),Adv. Atmos. Sci.,2012,第5作者 

(104) Can the Uncertainties of Madden–Jullian Oscillation Cause a Significant Spring Predictability Barrier for ENSO Events,Acta Meteorologica Sinica.,2012,第2作者 

(105) Effect of Stochastic MJO Forcing on ENSO Predictability,Adv. Atmos. Sci.,2011,通讯作者 

(106) A new strategy for solving a class of nonlinear optimization problems related to weather and climate predictability,Adv. Atmos. Sci.,2010,第1作者 

(107) An extension of conditional nonlinear optimal perturbation approach and its applications,Nonlin. Processes Geophys,2010,通讯作者 

(108) The “Spring Predictability Barrier” Phenomenon of ENSO Predictions Generated with the FGOALS-g Model,AOSL,2010,通讯作者 

(109) Is model parameter error related to spring predictability barrier for El Nino events,Adv. Atmos. Sci,2010,第1作者 

(110) Conditional nonlinear optimal perturbation: applications to stability, sensitivity, and predictability,Science in China (D),2009,第1作者 

(111) Dynamics of nonlinear error growth and season-dependent predictability of El Nino events in the Zebiak-Cane model,Quarterly Journal of Royal Meteorological Society,2009,第2作者 

(112)Decisive role of nonlinear temperature advection in El Nino and La Nina amplitude asymmetry,J. Geophysical Research,2009,第1作者 

(113) Exploring the initial error that causes a significant spring predictability barrier for El Nino events,J. Geophysical Research,2009,第1作者 

(114) 赤道高频纬向风强迫对ENSO强度的影响,气候与环境研究,2009,第2作者 

(115) Zebiak-Cane数值模式的可预报性分析,气候与环境研究,2008,第2作者 

(116) What kind of initial errors cause the severest prediction uncertainties for El Nino in Zebiak-Cane model,Adv. Atmos. Sci.,2008,通讯作者 

(117) Investigating a nonlinear characteristic of ENSO events by conditional nonlinear optimal perturbation,Atmospheric Research,2008,第1作者 

(118) Season-dependent dynamics of nonlinear optimal error growth and ENSO predictability in a theoretical model,Journal of Geophysical Research,2007,第1作者 

(119) A kind of initial errors related to “spring predictability barrier“ for El Nino event in Zebiak-Cane model,Geophysical Research Letters,2007,第3作者 

(120) Progress in predictability studies in China (2003-2006),Adv. Atmos. Sci.,2007,第1作者 

(121) Investigating decadal variability of El Nino-Southern Oscillation asymmetry by conditional nonlinear optimal perturbation,J. Geophysical. Research,2006,第1作者 

(122) Applications of conditional nonlinear optimal perturbation in predictability study and sensitivity analysis of weather and climate,Adv. Atmos. Sci.,2006,通讯作者 

(123) 用非线性最优化方法研究El Nino可预报性的进展与前瞻,大气科学,2006,第1作者 

(124) The Tangent Linear Model and Adjoint of a Coupled Ocean-Atmosphere Model and Its Application to the Predictability of ENSO,International Geoscience and Remote Sencing Symposium,2006,第2作者 

(125) 数值模式误差对降水四维变分资料同化及预报的影响,气候与环境研究,2006,第2作者 

(126) Applications of nonlinear optimization method to the numerical studies of atmospheric and oceanic sciences,Appl. Math. Mech.,2005,第1作者 

(127) Applications of nonlinear optimization methods to quantifying the numerical model for ENSO,Progress in Natural Sciences,2005,第1作者 

(128) Recent advances in predictability studies in China (1999-2002),Adv. Atmos. Sci.,2004,第2作者 

(129) Conditional nonlinear optimal perturbation as the optimal precursors for El Nino-Southern Oscillation events,J. Geophy. Res.,2004,第1作者 

(130) Chaotic and resonant streamlines in quasi-symmetric flows,Mathematic Applicata,2004,第1作者

科研活动

   
会议报告

国际/国内会议邀请报告 
(1) Wansuo Duan, Hui Xu, A study on ENSO asymmetry by conditional nonlinear optimal perturbation, Asia Oceanic Geosciences Society16-20 June, 2008, Busan,Korea. (邀请报告)
(2) Wansuo Duan, Mu Mu, Conditional nonlinear optimal perturbation and its applications to thestudies of ENSO predictability. 1st PRIMA conference, Sydney,Australia. 6-10 July, 2009. (30 分钟邀请报告)
(3) Wansuo Duan, Xinchao Liu, Mu Mu, Characteristic of initial errors that cause a significant springpredictability barrier for El Nino events. AOGS 2009, Singapore, 10-15 August,2009. (30分钟邀请报告)
(4) Wansuo Duan, Revealing a new feature of ENSO events, EGU2010, May 2-7, 2010, Vienna, Austria.(邀请报告)
(5) Wansuo Duan, MuMu, Conditional nonlinear optimal perturbation and its applications. CIMPAUNESCO THEMATIC SCHOOL, DATAASSIMILATION FOR GEOPHYSICAL FLUIDS, WUHAN (China), May 3 – May 14 , 2010 (60分钟邀请报告)
(6) 段晚锁,非线性最优化方法及其在天气和气候可预报性研究中的应用,全国流体力学数值方法研讨会,2011年8月,北京香山(大会邀请报告)
(7) Wansuo Duan, Wei Chao, The "spring predictabilitybarrier" for ENSO predictions and its possible mechanism: results from afully coupled model. EGU 2012 General Assembly,22-27 April 2012,Vienna,Austria.(特邀报告)
(8) Wansuo Duan, Yu Yanshan, Does model parameter error cause asignificant spring predictability barrier for El Nino events in the Zebiak-Canemodel? AOGS-AGU 2012 General Assembly,August 13-17 2012,Singapore (特邀报告)
(9) Wansuo Duan, Wu Yujie, Season-dependent predictability of PDO-related SST anomalies and its error growth dynamics. 中国海洋局海洋二所2013年度学术年会,杭州, 2014年1月7-9日。(特邀报告)
(10) Duan Wansuo,Nonlinear forcing singular vector and related predictability,2015 International Workshop on Control problem with PDE constraints and interface problems. Nanjing Normal University, Xianlin Campus from June 10 to June 12, 2015 (特邀报告)
(11) Wansuo Duan, Tian Ben, Constrasting initial errors that cause a significant "spring predictability barrier" for ENSO. IGU2015, Moscow, Aug. 17-21, 2015. (邀请报告)
(12) 段晚锁,ENSO预测的目标观测敏感区及其在热带太平洋海温多模式集合预报中的应用。ENSO和次季节-季节气候预测技术研讨会,成都,9月14-15日, 2015(邀请报告)
(13) 段晚锁,非线性强迫奇异向量方法及其在ENSO可预报性研究中的应用。中科院大气所2014-2015年度学术年会。北京,9月24日,2015(邀请报告)
(14) Wansuo Duan, Feng Rong, Mu Mu, Target observation of high-impact ocean-atmospheric environmental events. 全国气候系统研究学术研讨会,中国南京,11月25-27日, 2015(特邀报告)

(15) WansuoDuan, Tian Ben, Chen Lei, Li Xuquan, Comparison of initial errors most likely to cause a significant spring predictability barrier for two types of El Nino events. 西太平洋海洋环流与ENSO及中长期气候动力学研讨会, 青岛,12.7-8, 2015.(邀请报告)

(16) 段晚锁,构造集合预报初始扰动的新方法及其在台风预报研究中的应用,中国气象科学研究院年会,北京,1.7-8日,2016(特邀报告)

(17) Wansuo Duan, Ben Tian, Xuquan Li, Lei Chen, Sensitive areas for targeting observations associated with predictions of two types of El Nino events. COAA. Beijing, China. 07.27-30,  2016. (邀请报告)

(18) Wansuo Duan, Peng Zhao, The most disturbing tendency error of the Zebiak-Cane model associated with ENSO predictions. AOGS2016,  Beijing, China. 08.01-05, 2016. (邀请报告)

(19) 段晚锁,Target observations for two types of El Nino events and their role in reducing prediction uncertainties, 中国气象学会2016年度学术年会, 陕西西安,11,2-4,2016(邀请报告

(20) Wansuo Duan, Ben Tian, Xuquan Li, Target observation for improving initialization of two types of El Nino predictions. PAMS 2017, Jeju Island, South Korea, 4.11-13. 2017.(邀请报告)

(21) Wansuo Duan, An approach to generating mutually independent initial perturbations for ensemble forecasts: orthogonal conditional nonlinear optimal perturbations. International Conference on Random Dynamical Systems, Wuhan, China. 6. 24-27, 2017.(邀请报告)

(22) Wansuo Duan, Ben Tian,Target observations for improving initializations for two types of El Nino events predictions. AOGS2017, Singapore, 8.6-11, 2017.(邀请报告)

(23) 段晚锁,基于粒子滤波的目标观测新方法及其在两类El Nino可预报性研究中的应用。中国气象学会第34届年会, 河南郑州, 9,26-30, 2017。(邀请报告)

(24) Wansuo Duan, Target observations for improving initializations for two types of El Nino events predictions. BIRS workshop: Nonlinear and Stochastic Problems in Atmospheric and Oceanic Prediction.  Banff, Canada, 11.19-24, 2017.(邀请报告)

(25) Wansuo Duan,Tao Lingjiang, An ENSO forecast system based on an intermediate model and optimal forcing vector assimilation. AOGS2018. Hawaii, 6.2-8, 2018.(邀请报告)
(26) Wansuo Duan, Hou Meiyi, An approach to data analysis for predictability: application to two flavors of El Niño. AOGS2019, July 27-August 3, 2019, Singapore.(邀请报告)
(27) Wansuo Duan, Zhou Qian, Mu Mu, The Initial Errors Occurring in the Indian Ocean Temperature that Cause “Spring Predictability Barrier” for El Niño in the Pacific Ocean.AOGS2019, July 27-August 3, 2019, Singapore.(邀请报告)

(28) Wansuo Duan, A data assimilation approach for dealing with combined effect of kinds of model errors and its application.  第十三届全国海洋资料同化和数值模拟研讨会, 湖南长沙,12. 3-4, 2020. (邀请报告)

(29) 段晚锁,非线性最优化方法及其在数值天气预报和气候预测研究中的应用,第四届中国系统科学大会,青岛, 9. 19-20, 2020,(线上会议)(邀请报告)

(30) Wansuo Duan, Junjie Ma, Stephan Vannitsem, A novel ensemble forecasting method for dealing with combined effect of the initial error and the model error and its potential deep learning implementatio. AOGS2022, August 01-05, 2022, Singapore. (邀请报告)




国内会议


第一届大气、海洋可预报性研讨会 

第二届大气、海洋可预报性研讨会

第三届大气、海洋可预报性研讨会


第一届“非线性最优化方法在大气与海洋科学中的应用”夏季讲习班

第二届“非线性最优化方法在大气与海洋科学中的应用”夏季讲习班

第三届“非线性最优化方法在大气与海洋科学中的应用”夏季讲习班


台风目标观测研究与外场试验研讨会


国际会议

1. Youmin Tang, Wansuo Duan,Shouhong Wang, Mu Mu, Olivier Talagrand, 在19-24 November 2017于加拿大班夫BIRS workshop,召集分会:Nonlinear and Stochastic Problems in Atmospheric and Oceanic Prediction.
2. Local co-chair Wansuo Duan, Ruiqiang DingInternational Commission on Dynamical Meteorology (ICDM) workshop: Dynamics andpredictability of high-impact weather and climate events(国际会议),ICDM2012 workshop,  6-9 July, Kunming, China.


国际会议分会

1. Wansuo Duan, Chun-Chieh Wu, Hyun Mee Kim, 在2009年8月AOGS2009国际会议组织可预性分会: AS05: Predictability of weatherand climate: theory and applications.

2. Wansuo Duan,F.X. Le Dmiet, Youmin Tang, Kyun mee Kim, 于2010年在印度召开的AOGS2010国际会议组织可预报性分会。AS12:Predictability of weatherand climate: theory, methodology, and applications.

3. Mu Mu, Wansuo Duan, 于2010年5月在Vienna召开的EGU2010国际会议组织可预报性分会:NP5.3 Nonlinear optimal mode andits applications in predictability, sensitivity, and stability.

4. Zoltan Toth, Wansuo Duan, S. Vannesti 等,于2011年4月在Vienna召开的EGU2011国际会议组织可预报性分会:NP5.3:Nonlinear instability and predictability.

5. Mu Mu, Wansuo Duan, S. Vannesti 在22-27 April 2012于Vienna-EGU 2012 GeneralAssembly国际会议组织可预报性分会:NP5.3:Nonlinear optimal mode andrelated predictability, sensitivity, and stability.

6. Wansuo Duan, F. Sellevec, Peter J. Vanllevon,在 13-17August 2012 于新加坡AOGS-AGU 2012 GeneralAssembly 国际会议组织可预性分会:AS39: Predictability ofweather and climate: theory, methodology, and applications.

7. Mu Mu, Wansuo Duan, S. Vannesti, , 在 April, 2013于奥地利维也纳EGU 2013 General Assembly组织可预报性分会:NP5.3: Error growth dynaimics and related predictability for weather and climate.

8. Mu Mu, S. Vannesti, Wansuo Duan, 在28 April-2 May, 2014于奥地利维也纳EGU 2014 General Assembly组织可预报性分会:NP5.3: Initial error dynamics and model error physics in weather and climate predictability studies.

9. Shaocheng Xie,Wansuo Duan,Kuan-Man Xu,Masahiro Watanabe等,在28 Jul to 01 Aug, 2014于日本札幌AOGS 2014 General Assembly召集可预报性分会:AS08-13: Predictability Problems and Systematic Errors in Numerical Weather and Climate Prediction: Theory, Modeling and Evaluation

10. Mu Mu, S. Vannesti, Wansuo Duan,在12 – 17 April 2015于奥地利维也纳EGU 2015 General Assembly召集可预报性分会NP5.3: Initial error dynamics and model error physics in weather and climate predictability studies

11. Wansuo Duan,Stephane Vannitsem,Tieh-Yong Koh,在2-7Aug, 2015于新加坡AOGS 2015 General Assembly召集可预报性分会:AS28:Predictability of Weather and Climate: Theory, Methodology and Applications

12. Olivier Talagrand, S. Vannesti, Wansuo Duan, etc,在17-22 April 2016于奥地利维也纳EGU 2015 General Assembly召集可预报性分会NP5.2: Inverse problem of data assimilation, Initial error and model error

13. Zheng Fei, Noel Keenlyside, Wansuo Duan, Stephane Vanisstem, et al., 于1-5 August 2016在AOGS2016 召集可预报性分会:OS08-AS16: Advances In Data Assimilation And Ensemble Forecast: Applications To Studies And Predictability Of Atmosphere-ocean Variability

14. Zhang Ronghua, Wang Dongxiao, Wansuo Duan , 在27--30 July 2016全球华人大会大气海洋科学大会暨第七届COAA国际大气和海洋气候变化会议召集分会:Session Title: Ocean process and modelling

15. Olivier Talagrand, Stéphane Vannitsem, Wansuo Duan, Amos Lawless, Matthew Martin, Alberto Carrassi, Javier Amezcua, 在24–29 April 2017 于奥地利维也纳EGU 2017 General Assembly召集分会: NP5.1: Inverse Problems, Data Assimilation and Error Dynamics.

16. Mu Mu, Wansuo Duan, Stéphane Vannitsem. 在24–29 April 2017 于奥地利维也纳EGU 2017 General Assembly召集分会: NP5.2: Initial error dynamics and model error physics in predictability studies of weather and climate.

17. WanSuo Duan, Youmin Tang, Mu Mu, Zhijin Li. 在4-8 June 2017于加拿大多伦多CMOS 2017 Congress召集分会:1704061 Data Assimilation, Ensemble Prediction, and Intrinsic Predictability.

18. Craig H. Bishop, Weijia Kuang, Wansuo Duan, Andrew Moore等,在27 August-1 September 2017南非开普敦IAMAS-2017会议召集分会:JA3 - Frontier Challenges In Data Assimilation And Ensemble Forecasting ForThe Atmosphere, Ocean And Solid Earth (IAGA, IAMAS, IAPSO) .

19. Stéphane Vannitsem,Wansuo Duan,Noel Keenlyside,Fei Zheng,在2-8 June 2018于Hawaii AOGS2018 General Assembly召集分会:AS36 - Ocean-atmosphere Coupling: Dynamics, Assimilation, and Predictability.

20. Olivier Talagrand, Javier Amezcua, Alberto Carrassi, Amos Lawless, Mu Mu, Wansuo Duan, Stéphane Vannitsem. 在7–12 April 2019 于奥地利维也纳EGU 2019 General Assembly召集分会: NP5.1: Data assimilation, Predictability, Error Identification and Uncertainty Quantification in Geosciences.

21. Mu Mu, Alexander Feigin, Wansuo Duan, Jürgen Kurths, Stéphane Vannitsem在4-8 May, 2020,EGU2020 General Assembly 召集可预报性分会:NP5.2 New approaches to predictions and predictability estimation for geophysical fluid. On-line

22. Vena Pearl Bongolan, Wansuo Duan, and Ramsundram Narayanan. AOGS2021: IG02 Natural Hazards and Disaster Risk. Virtual meeting from Singapore.1-6 August 2021.

23. Vena Pearl Bongolan, Wansuo Duan, Ramsundram Narayanan, James Terry. AOGS2022: IG31-Natural Hazards and Disaster Risk. August 01-05, 2022, Singapore.


主持的科研项目

1. 国家自然科学基金-重点项目
项目名称:非线性强迫奇异向量-集合预报方法及其在厄尔尼诺和台风可预报性研究中的应用
项目编号:41930971
执行年限:2020.01-2024.12
 
2. 国家杰出青年科学基金
项目名称:厄尔尼诺-南方涛动可预报性的非线性误差增长理论及其应用研究
项目编号:41525017
执行年限:2016.01-2020.12
 
3. 国家自然科学基金-面上项目
项目名称1:北太平洋海温“夏季可预报性障碍”现象及其误差增长动力学研究
项目编号:41376018
执行年限:2014.01-2017.12
 
项目名称2:非线性强迫奇异向量及其在 ENSO 第二类可预报性研究中的应用
项目编号:41176013
执行年限:2012.01-2015.12
 
4. 国家自然科学基金-青年基金
项目名称:用条件非线性最优扰动研究 ENSO 可预报性的年代际变化问题
项目编号:40505013
执行年限:2006.01-2008.12
 
5. 国家重点基础研究发展计划-课题
课题名称1:台风目标观测研究
课题编号:2018YFC1506402
执行年限: 2018.12-2021.12
 
课题名称2:东亚季风气候年际-年代际变率及人类活动影响的模拟及预测研究
课题编号:2012CB955202
执行年限: 2012.0 1-2016. 12
 
6. 中科院知识创新工程重要方向项目
项目名称:ENSO可预报性年代际变化若干关键问题的研究
项目编号:KZCX2-YW-QN203
执行年限:2010.01-2012.12

课题成员

在职职工

孙国栋,研究员;研究方向:陆面过程模拟不确定性
周菲凡,副研究员;研究方向:台风可预报性
秦晓昊,副研究员;研究方向:台风可预报性
冯蓉,副研究员;研究方向:印度洋偶极子可预报性
徐辉,助理研究员;研究方向:ENSO可预报性
杨丽超,博士后;研究方向:大气环境气象学及可预报性

 

已毕业学生

2022届

姜琳,博士,山东大学海洋研究院;李文瑶,硕士,兰州中心气象台

2021届

姚佳伟,博士,国家海洋环境预报中心

2020届
陶灵江,博士,复旦大学;侯美夷,博士,河海大学
2019届
温茜茜,博士,中科院南海海洋研究所
2018届
刘娜,硕士,北京英视睿达科技有限公司;李绪泉,博士,嘉实基金管理有限公司;刘达,博士,国家气象中心;齐倩倩,博士,国家气象中心;汪叶,博士,河南大学
2017届
黄朝铭,博士,江西农业大学
2016届
胡均亚,博士,中国科学院海洋研究所;封凡,博士,成都信息工程大学;霍振华,博士,国家气象中心
2015届
武于洁,博士,中国气象局国家气候中心;宋林烨,博士,北京城市研究所;陈磊,博士,上海市气象局;张璟,博士,美国NOAA
2014届
赵  鹏,博士,中国气象局培训中心;田奔,博士,国家气候中心
2012届
张蕊,硕士,美国
2011届
张雅乐,博士,中国气象局培训中心;彭跃华,硕士,大连
2010届
魏  超,硕士,国家气候中心
2007届
刘新超,硕士,四川省气象局

 
在读学生

2021级

李永辉,硕士生;侯雨轩,硕士生;庄逸,直博生;张晶晶,博士生,台风可预报性

2020级

茹易,硕士生,IOD可预报性;汪小云,博士生,MJO可预报性

2019级
胡蕾,博士生,ENSO集合预报
2018级
张晗,博士生,热带气旋集合预报;张一驰,博士生,热带气旋可预报性;郑颖聪,博士生,ENSO可预报性;麻俊杰,博士生,机器学习和集合预报